1996 soccer game in the Midwest, (Rick Dikeman image)

Nouméa ground station after the flood

A pencil and a coffee cup show the size of NASA’s teeny tiny PhoneSat

Bonus Hotspot: Naro Tartaruga AUV

Pacific lamprey spawning (photo by Jeremy Monroe, Fresh Waters Illustrated)

“Return of the Bucentaurn to the Molo on Ascension Day”, by (Giovanni Antonio Canal) Canaletto

The U.S. Naval Observatory Alternate Master Clock at 2nd Space Operations Squadron, Schriever AFB in Colorado. This photo was taken in January, 2006 during the addition of a leap second. The USNO master clocks control GPS timing. They are accurate to within one second every 20 million years (Satellites are so picky! Humans, on the other hand, just want to know if we’re too late for lunch) USAF photo by A1C Jason Ridder.

Detail of Compass/ BeiDou2 system diagram

Hotspot 6: Beluga A300 600ST

Tracking illegal logging in Romania, autonomous mining, ancient calendars and Canadian cows

Tracking illegal logging in Romania, autonomous mining, ancient calendars and Canadian cows

1. Ghost trucks tracked
Romania
√ Every day on Romania’s highways, “ghost trucks” slip by unnoticed. Digital records show the vehicles, loaded with timber, coming from verified logging sites in the Romanian forest. But the GPS data associated with the records reveal they actually have much more random origins: from cornfields, to cemeteries, to California. It’s part of an illegal logging industry the government has said removes an estimated 141 million cubic feet of timber each year for the country’s old growth forests, some of the last in Europe. But a new, high-tech solution from Romania’s Ministry of the Environment is designed to counteract illegal logging by putting as much information as possible in the hands of the public using satellite imagery and GPS tracking. The new system, launched in December, is called Inspectorul Padurii, which means “Forest Inspector.” It works by combining images from three different satellites, taken at least once every five days. This information is used to help spot illegal logging.

2. Mining autonomously
Australia
√ Trucks the size of a small two-story house without a driver or anyone else on board. Mining company Rio Tinto has 73 of these titans hauling iron ore 24 hours a day at four mines in Australia’s Mars-red northwest corner. At one, known as West Angelas, the vehicles work alongside robotic rock drilling rigs. The company is also upgrading the locomotives that haul ore hundreds of miles to port — the upgrades will allow the trains to drive themselves, and be loaded and unloaded automatically. Rio Tinto intends its automated operations in Australia to preview a more efficient future for all of its mines — one that will also reduce the need for human miners. The rising capabilities and falling costs of robotics technology are allowing mining and oil companies to reimagine the dirty, dangerous business of getting resources out of the ground. Rio Tinto uses driverless trucks provided by Japan’s Komatsu. They find their way around using precision GPS and look out for obstacles using radar and laser sensors.

3. Calendar Rock
Italy
√ Italian archaeologists have found an intriguing Stonehenge-like “calendar rock” in Sicily. Featuring a 3.2-foot diameter hole, the rock formation marked the beginning of winter some 5,000 years ago. The holed Neolithic rock was discovered Nov. 30, 2016 on a hill near a prehistoric necropolis six miles from Gela, on the southern coast of Sicily, by a team who was surveying some World War II-era bunkers. Using a compass, cameras and a video camera mounted to a GPS-equipped drone, archaeologist Giuseppe La Spina and colleagues carried out a test in December at the winter solstice. The idea was to find out if the rising sun at solstice aligned with the distinct hole in the rock feature. According to La Spina, the experiment was “a total success.” At least two other holed stones have been found in Sicily in the past.

4. Cow Heard
Canada
√ In the mid-’70s, as a research scientist at the Melfort Research Station, Duane McCartney helped Saskatchewan Agriculture evaluate the first button-type electronic ear tags on their cows at the Pathlow pasture research project. At the time, he also had a big satellite remote sensing project to monitor pasture productivity, and would tell colleagues that the goal was to develop a system whereby he could sit in his office back in Melfort and monitor and remotely move the cows to different paddocks. They all laughed back then, but now it is a reality. There are some exciting innovations on the horizon for managing grazing operations, and recently Saskatoon was host to over 500 rangeland researchers and managers from 48 different countries at the International Rangeland Congress. The event featured over 500 presentations on all sorts of topics involving rangeland management. With the theme of “Managing the World’s Rangelands and Wild Lands in a HighTech World” it provided a forum for some very interesting capabilities of computers, cellphones, internet and satellite remote sensing for enhanced rangeland management.

The post GNSS Hotspots | January 2017 appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Sometimes, of course, unpredictability is in the immanent nature of things. Despite advances in meteorological technology and science, weather continues to prove fickle. Foreknowledge of earthquakes remains difficult to pin down in space and time.

As with the notion of “disruption,” unpredictability can be useful. A move in chess or go, for instance. Or in the case of cuisine — say, when usurping Taco Thursday with chicken tagine. Even in negotiations, an unanticipated gambit can change the outcome positively.

Sometimes, of course, unpredictability is in the immanent nature of things. Despite advances in meteorological technology and science, weather continues to prove fickle. Foreknowledge of earthquakes remains difficult to pin down in space and time.

In matters of infrastructure, however, unpredictability is rarely a plus. Discontinuing a bridge project halfway across the river is an expensive exercise. Eliminating a health insurance program can bring unforeseen consequences.

So it is with GNSS programs. Engineering change orders are an expensive proposition that have — as with many military technology innovations — bedeviled the program since the beginning. Mid-program changes in requirements or addition/ subtraction of capabilities have often put GPS modernization on a long and winding road.

Simply implementing planned upgrades is hard enough — satellite-ranging cross-links, for example, still not fully operational 20 years after conception. Accommodating unplanned changes are even more so.

The good news is that — after years of starts, stops, and course corrections; after budgetary underfunding and interventions by agencies outside those primarily responsible for the program (think Congress or the Federal Communications Commission); after long policy battles and unrealized mandates, after years of blood, sweat, and tears spent in wrestling a comprehensive and stable enterprise out of the competing motives and goals of myriad players, after all this — GPS is on relatively solid ground with a relatively clear way ahead.

The 2017 National Defense Authorization Act, passed in December by the last bipartisan Congress that we’ll see for a couple of years, funds the program in most of its parts and provides guidance on issues of a backup system, frequency protection, critical infrastructures, and use of other GNSS systems by U.S. citizens and military services.

The International Committee on GNSS (ICG) continues to reconcile operational practices and technical policies to optimize the utility of multiple systems. Bilateral agreements are taking compatibility and interoperability even further.

If Congress puts our tax money where its mouth is and matches authorization with 2017 appropriations, then the GPS program will be in good shape — absent a U-turn when the bill arrives at the White House.

Indeed, the known knowns seem likely to outweigh the known unknowns. As for perhaps the leading unknown unknown, a new commander in chief, well, stay tuned to your SMS provider.

Omnibus legislation such as a $619-billion budget makes a tempting target for whim and vendetta, for superficial micro-managing.

Perhaps it will be enough to mention that Twitter ultimately depends on effective and stable GPS timing. (Yes, we can assert that caveat in far less than 140 characters.)

But, more likely, GPS/GNSS- stakeholders — within and outside government, in the United States and abroad, among users and providers — will need to stand ready to protect hard-won equities against caprice and transient temperament. A 44-year legacy and institution must necessarily trump the passing fancies or fantasies of term-limited politicians and administrations.

The post No Sudden Moves appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

The BeiDou Navigation Satellite System (BDS) is China’s contribution to the world in the domain of Global Satellite Navigation System (GNSS). The BDS is being developed by the Chinese government, mainly through military departments, with key considerations for China’s national security, economic interests and social progress.

The BeiDou Navigation Satellite System (BDS) is China’s contribution to the world in the domain of Global Satellite Navigation System (GNSS). The BDS is being developed by the Chinese government, mainly through military departments, with key considerations for China’s national security, economic interests and social progress.

After decades of development, the BDS has been recognized as one of the four big players in the field of GNSS. China has also started the development of a comprehensive positioning, navigation and timing (PNT) system with enough capabilities for air, sea, land, underground and underwater terminals, and the BDS is designed as the most important component.

From a structural point of view, the BDS is similar to the other GNSSs and composed of the satellite constellation, distributed ground facilities — including master control stations, uplink stations, and monitoring stations — and user receivers. One special feature is the inclusion of 5 geostationary satellites, raising the number of satellites in the constellation to 35. Another differentiator from the U.S. GPS, Russian GLONASS, and European Galileo system is its unique function of short message communications and position reporting capability, benefiting from the Chinese government’s strong support on both technical and financial aspects.

The BDS is designed and developed as a space infrastructure of national significance to offer two basic services: an open service free of charge and an authorized service with higher quality and integrity. At the current stage, applications based on the BDS are gradually penetrating to every corner of people’s lives and economic activities in the Asia-Pacific Region, particularly for meteorological observation, transport management and search & rescue.

Strategy of the BDS Development
Bearing in mind the mature technology and the policy of free access to open signals provided by GPS, many questions arose about why China should make substantive efforts to develop its own GNSS. However, in addition to the economic benefits created by the navigation industry, developing a domestically controlled GNSS was considered as a national security advantage.

Back in 1996 when the third Taiwan Strait Crisis started, two Chinese missiles failed to reach their targets during an exercise. Chinese military authorities believed that the event occurred due to the U.S. denial of GPS signals. Since then, China decided to develop a satellite navigation system under its own control and to complete the construction of the first generation of the BDS (BDS-1) at the beginning of 21st century.

However, as the BDS-1 was just a regional system with little commercial value, the Chinese government accepted the invitation from the European Union (EU) to join the Galileo program, with the ultimate goal of challenging the monopoly of the U.S. GPS. However, due to certain disagreements with the European Union, including China’s claim of being excluded from the key decision-making process and technical cooperation in the Galileo program, China decided to re-focus its attention on constructing its own GNSS.

Currently, China ranks the BDS as one of the key national technical projects, supported by specific funding; the BDS program is organized pursuant to a three-step strategy: (1) the construction of BDS-1, which was finished in 2000, with the goal of providing services over all of Chinese territory; (2) the construction of the BDS-2, which has been in operation since 2012 with the purpose of covering the Asia-Pacific region; (3) the deployment of the full constellation of BDS satellites, scheduled for completion by around 2020 and intended to offer global services.

Governance Structure of the BDS
Similar to GPS and GLONASS, the BDS is a dual system used for both military and civilian purposes. However, no official source has yet affirmed that the BDS is developed and exclusively controlled by Chinese military departments, despite a widespread belief that many ties exist between the BDS and Chinese People’s Liberation Army. Official publications about the BDS simply use the expression “Chinese government” or “China”.

Furthermore, no official information on the governance structure of the BDS has been formally released, even though a general framework of BDS-related authorities can be drawn out through available open news reports and documents about the BDS. The key organizations involved in the BDS program are the following:

The China Satellite Navigation Committee (中国卫星导航系统委员会, hereinafter referred to as the CSNC). The CSNC seems to be the top decision making organ on the fundamental strategy and policy of the BDS and other Chinese PNT systems. On the one hand, the CSNC gives the opening address to the annual China Satellite Navigation Conference, which shows its important position in the supervisory framework of the BDS for domestic activities. On the other hand, the CSNC has also been working thus far as the leading authority for international cooperation involving the BDS. For example, the CSNC, on behalf of China and as the chairman of the Chinese side of China-Russia Cooperation Program Committee on Satellite Navigation, signed the “China’s BeiDou System and Russian GLONASS System Compatibility and Interoperability Cooperation Joint Statement” with the former Russian Federal Space Agency (currently known as the State Space Corporation ROSCOSMOS) in 2015.

The China Satellite Navigation Office (中国卫星导航系统管理办公室, CSNO). Under the leadership of the CSNC, the CSNO is in charge of the management work of the BDS. The CSNO is a joint office established by the competent governmental departments involved in BDS activities. For now, the CSNO is working on the system construction, application promotion, and industrialization of the BDS.

To aid in making scientific management and technical decisions, the CSNO is supported by its two internal branches, namely the Expert Committee and the Expert Teams. In addition, the CSNO is responsible for releasing top-level official policies and technical documents on the BDS both in Chinese and English as well as approving the documents on BDS-related performance and standard criteria. The CSNO also operates the official website of the BDS.

The Central Station for Satellite Navigation (卫星导航定位总站, hereinafter the CSSN). The CSSN is the Navigation Force under the leadership of Joint Staff Department of the Central Military Commission (formerly known as the General Staff Department of Chinese People’s Liberation Army). The CSSN was established as the agency for the management and operation of the BDS in 1999. Although the competence of the CSSN was described as “the research, demonstration, development, operation and application guarantee of the BDS,” it focuses more on the operation of the control segment comprising various ground stations of the BDS.

The China National Administration of GNSS and Applications (中国卫星导航定位应用管理中心, CNAGA). The CNAGA is the functional department for the application management of the BDS, which is contributing to promote the large-scale industrialization and international development of the BDS. Specifically, the CNAGA has an announced commitment to the following four aspects of the BDS:

• management of the operation and maintenance of the BDS, so as to ensure the successive and reliable provision of BDS services;
• supervision over the manufacturing enterprises of BDS user segments, so as to ensure the quality and safety of BDS services; 
• development of basic application criteria and critical infrastructure of the BDS, so as to consolidate the basis of application development; 
• the establishment of innovation platforms in terms of an industry alliance, industry base, industry forum and international cooperation for the BDS, so as to promote the communication and cooperation among businesses.

The National Technical Committee on BeiDou Satellite Navigation of the Standardization Administration of China (全国北斗卫星导航标准化技术委员会, hereinafter the NTCBDSSA). The NTCBDSSA was established in 2014 and is under the joint leadership of the Standardization Administration of the People’s Republic of China (SAC) and the Equipment Development Department of the Central Military Commission (formerly known as the General Armaments Department of Chinese People’s Liberation Army).

The NTCBDSSA is composed of 48 members, 7 observers and 3 liaisons, and the China Satellite Navigation Engineering Center (中国卫星导航工程中心) and the China Astronautics Standards Institute (中国航天标准化研究所) jointly comprise its secretariat. The competence scope of the NTCBDSSA covers the standardization activities concerning the management, construction, operation, application and service of the BDS. It is also in charge of developing civilian and military standards for the BDS both at the international and national level. However, all the standards proposed by the NTCBDSSA have to be approved by the CSNO before they come into force.

Based on the foregoing description, we may conclude that, in the context of the BDS, three main organizations have active roles: 1) the CSNO is responsible for the deployment and maintenance of the space segment, 2) the CSSN is operating the control segment, and 3) the CNAGA deals with supervision of the user segment, including the manufacturing of user receivers and the provision of PNT services.

In addition to these entities, as the BDS is a complicated system with interdisciplinary participation and cross-sectional dimension, many other authorities are involved in the management framework of the BDS. For example, the frequency protection of the BDS within the Chinese territory is under the responsibility of the Bureau of Radio Regulation of the Ministry of Industry and Information Technology of China, which is also known as the State Radio Office.

Policy and Law of the BDS
Different from its competitors in the domain of satellite navigation, particularly the EU and the United States, China owns a unique socialist system of laws with Chinese characteristics. China has recently placed great emphasis on the fundamental principle of governing the country by law. Accordingly, the rule of law has been proposed very frequently for China’s space industry.

However, China is still one of a few space powers that lacks a basic space law. Therefore, setting up a comprehensive legal framework for the BDS will arguably require some time. Until that can be achieved, a series of policy documents would have to retain the dominant role, even though policy solutions are much less effective than legal arrangements in the Chinese context. These include the following policy documents:

White Paper on China’s Space Activities. This white paper is currently the basic document relating to China’s space policy, and it always places great importance on the development of the BDS. The document has thus far been updated to the fourth version in 2016.

After summarizing certain achievements in the field of the BDS since 2006, the third version (2011) addresses the three-step strategy of the BDS and lists the BDS as one of the priority projects in key fields; the latest version (2016) requires the improvement of BDS applications and promotion of international cooperation of the BDS.

White Paper on China’s BeiDou Navigation Satellite System. This white paper was released in June 2016, which makes it the latest policy document concerning the BDS specifically. This white paper lays down the goals and principles related to the development of the BDS and again addresses the BDS three-step strategy.

According to the document, China is committed to ensuring the safe and reliable operation of the BDS and providing continuous, stable and reliable open services to users free of charge. In addition to protecting the utilization of the BDS frequency spectrum, the white paper also requires promotion of BDS applications and industrial development by taking multiple measures, as follows: 

• establishing an industrial supporting system, through making industrial policies, building equitable market environment, enhancing standardization process, and building a comprehensive service system of location data;
• establishing an industrial application promotion system, through improving the BDS application in key sectors related to national security and economy, pushing forward close integration of the BDS with state strategy on industrial and regional development, guiding mass market applications of the BDS in the fields of smart phones, vehicle-borne terminals, and wearable devices; 
• establishing an industrial innovative system, by enhancing the research and development of basic products based on the BDS, encouraging and supporting the construction of a technology innovation system that relies on the market players as the main factor combined with the efforts of academic institutes. The industrial system is called on to promote the integrated development of the BDS with infrastructures and technologies including the “Internet+”, “Big Data”, the “Internet of Things”, communications, remote sensing, and other emerging industries.

As for international cooperation of the BDS, the Chinese government plans to further the efforts by

• strengthening compatibility and joint applications with other navigation satellite systems;
• using frequency and orbital slot resources according to international rules, particularly the Radio Regulations by the International Telecommunication Union (ITU); 
• promoting the ratification of the BDS in accordance with international standards, particularly those of the International Civil Aviation Organization (ICAO) and the Third- Generation Mobile Communication Standard Partnership Project (Note that the BDS already gained recognition from the International Maritime Organization (IMO) in November 2014); 
• participating in multilateral activities in the field of international satellite navigation, such as the conferences and academic exchanges hosted by the International Committee on Global Navigation Satellite Systems (ICG); 
• promoting international applications of the BDS by intensifying publicity and popularization of the BDS, and implementing internationalization projects in the field of policy, market, law and finance, and so forth.

Medium and Long Term Development Plan for China’s Satellite Navigation Industry. This policy document was approved by the State Council and released by its General Office in September 2013. The Plan makes overall arrangements for medium- and long-term development of the BDS and other satellite navigation industry developments. The Plan first analyzes the current situation of satellite navigation that the BDS faces at home and abroad; second, it lays down the guidelines and principles to develop China’s navigation industry.

More importantly, the development plan indicates the year of 2020 as the critical timeline for China to form a new innovation-oriented development pattern. To achieve that goal, the development plan lays out six specific directions and tasks and five major projects to develop BDS-related industry before the year of 2020. Several measures are proposed to support this initiative.

Several Opinions on the Promotion of Geo-information Industry Development. This policy document was released by the General Office of the State Council in January 2014 with the purpose of promoting the development of China’s geo-information industry as a whole. Accordingly, the industry development of the BDS is an important element to allow the integration between geo-information and PNT services, which is recognized as an important way to facilitate people’s lives.

Several Opinions on Promotion and Application of the BeiDou Satellite Navigation System by China’s National Administration of Surveying, Mapping and Geo-information. This policy document was issued by China’s National Administration of Surveying, Mapping and Geo-information in March 2013, with the purpose of implementing the prior policy documents. This policy document obviously was made from the perspective of BDS users. It urges the competent regional authorities on surveying, mapping and geo-information to accelerate the promotion of application and industrialization of the BDS, and to safeguard China’s national security and interest within their competence.

Provisions of the Chinese People’s Liberation Army on the Administration of the Satellite Navigation Application. This military rule was issued by the former General Staff Department of Chinese People’s Liberation Army (currently known as Joint Staff Department of the Central Military Commission) and became effective on June 1, 2014. Although it has a lower status than “law” or “regulation”, this “rule” for now is the only legal-binding document in effect that relates directly and specifically to BDS applications.

The full text of this rule is not open to the public; however, the rule is known to be structured in 7 chapters, containing 36 articles, which specify the duties and responsibilities, programming and planning, application and approval, organizations, technical support, and security management regarding utilization of the BDS by Chinese military troops, particularly in combat situations.

In addition, some normative documents having no legal effect play an important role in the specific management of BDS-related activities. These documents are issued by

• the CNAGA, for example: Quality Management Provisions for BeiDou Civil Service, Authorized Management Methods of Quality Inspection Agencies for BeiDou Products, Performance Standard of Shipborne BeiDou Receiving Devices, and other authoritative information regarding BDS application management, certification of the BDS service and application, and inspection of BDS products’ quality;
• the CSNO, for example: BeiDou Navigation Satellite System Signal In Space Interface Control Document Open Service Signal, BeiDou Navigation Satellite System Open Service Performance Standard, Terminology for BeiDou Navigation Satellite System (BDS), and 16 other standards prepared especially for the BDS.

Way Forward
Although China has made great achievements on the research, development, and construction of the BDS system, China’s deployment of the management of the BDS, including institutional, policy, and legal arrangements, is still in its infancy. This may, somewhat, clip the wings of its development, operations, and applications and may constrain its further popularization both at domestic and global level.

Although a vague governance structure has been delineated by the authors based on the currently available materials, the respective roles and responsibilities for the BDS still have to be well defined and disclosed in the form of law. The overlapping of responsibilities between the CSNO and the CNAGA should not be ignored. More importantly, a civilian-military coordination mechanism should be developed as soon as possible in order to promote the development of civil applications and to increase BDS commercialization both at internal and international level.

It is true that the strategy, goals, principles and action plans for the BDS are reflected by several policy documents, but none of them assigns specific tasks to each department; this inconsistency potentially compromises the implementation and enforceability of BDS policies in practice. Even though a law related to the BDS would be more legally binding than the planning and opinions that we have described here, only one classified military rule is available thus far for China’s GNSS program.

Fortunately, a regulation on satellite navigation proposed by the Equipment Development Department of the Central Military Commission has been listed into the Research Items of the State Council Legislative Workplan for 2016, as one of the of Legislative Projects Related to Implementing the National Security Strategy and to Protecting National Security. Even though the term “Research Items” represents low priority, at least it lights up the hope for a future legal regulation of the BDS.

Additional Resources
[1] BeiDou Satellite System (BDS), official website.
[2] China National Administration of GNSS and Applications, official website.
[3] China Satellite Navigation Office, Report on the Development of BeiDou Navigation Satellite System, Version 2.2, December 2013
[4] China Satellite Navigation Office, BeiDou Navigation Satellite System Open Service Performance Standard, Version 1.0, December 2013
[5] China Satellite Navigation Office, BeiDou Navigation Satellite System Signal In Space Interface Control Document Open Service Signal, Version 2.0, December 2013
[6] State Council Information Office of the People’s Republic of China, China’s BeiDou Navigation Satellite System (Foreign Languages Press, 2016).

The post State of Play in China appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

A: GNSS jammers are an ongoing threat to the reliable use of GNSS. The problem of geolocating GNSS jammers can be addressed using a time-difference-of-arrival (TDOA) processing technique; however, this problem is quite different than geolocating jammers in other radio frequency systems. The two main differences are:

(1) No GNSS are available to use as a timing reference.

Q: Is it possible to build a low-cost system to detect and locate a single GNSS jammer in near-real time?

A: GNSS jammers are an ongoing threat to the reliable use of GNSS. The problem of geolocating GNSS jammers can be addressed using a time-difference-of-arrival (TDOA) processing technique; however, this problem is quite different than geolocating jammers in other radio frequency systems. The two main differences are:

(1) No GNSS are available to use as a timing reference.

(2) The signal of interest (i.e., the GNSS signals) are weak. This contrast with other applications (e.g., mobile phone jamming) where the signal of interest is much stronger.

The first point forces the TDOA technique to be unconventional, but still possible. The second point eliminates the complexities of having to discern desired versus undesired signals in the band.

To address these issues the Communications Research Centre (CRC) Canada, which is the Government of Canada’s primary laboratory for wireless research, has been doing work in this area. Two complementary systems were devised to solve the problem of geolocating a single GPS jammer: iGeoLoc_GPS (interference Geolocation) and jAware_GPS (jammer situational awareness). iGeoLoc_GPS can geolocate GPS band interference, but the effect on a GPS receiver is unknown. jAware_GPS can indicate if a GPS receiver is jammed, but not geolocate the jammer source.

The iGeoLoc_GPS uses a 5 MHz bandwidth centered at GPS L1. The jAware_GPS examines all outputs of a GPS timing receiver for both timing and position errors and other irregularities.

In order to facilitate testing with an illegal device, a typical GPS chirp jammer was frequency-translated to a nearby experimental-licensed band and will be referred to as the translated- jammer. The “jammer” will refer to a signal source originating from either an intentional jammer device or a source of unintentional interference. Intentional or not, both sources can degrade a GPS receiver.

System Level
First, let’s take a look at the overall jammer detection systems under consideration.

jAware_GPS Description. In some cases only awareness that the onsite GPS signal is being disrupted is required. jAware_GPS is meant to answer the question: “Do we have a jamming problem?”

This stationary sensor uses the number and received power of satellites, positional drift, GPS receiver lock status, and the accuracy of the pulse-per-second (PPS) output to determine the status of a GPS receiver. The PPS error is measured using the internal phase meter of a chip scale atomic clock (CSAC).

The phase meter measures the time difference, with a resolution of 450 picoseconds, between the internal CSAC 1 PPS and the externally applied PPS from the GPS receiver. In order to use the phase meter the CSAC is always configured in 1 PPS discipline mode with a 10-second time constant, and the PPS time difference is reported once a second (cycle to cycle) in nanoseconds. If the PPS time difference exceeds 10 nanoseconds, the position drifts more than a threshold, or a sudden change occurs in satellite information, a GPS outage is reported until the signals are stable for 10 seconds.

iGeoLoc_GPS Description. The current iGeoLoc_GPS (Figure 1) uses four semi-transportable sensing nodes (A, B, C and D) connected in two separate networks: a real-time data network and a Wi-Fi control network.

Each sensing node receives the translated-jammer band and retransmits it in its own dedicated backhaul band to the processing node (Figure 6, 8, and 9). This continuous real-time frequency translation is referred to as the data network.

The jammer geolocation is calculated at the processing node using a TDOA technique followed by a geolocation algorithm. No waveform assumptions are used. A blind cross-correlation is computed between all pairs of sensing node datasets to determine their relative time differences of arrival.

A common jammer signal must be detected by at least three sensing nodes. This permits at least two time differences to be calculated and then used to generate possible hyperbolic intersections and hence possible geolocation points (in the horizontal plane).

The TDOA cross-correlation and geolocation processing works with 2¹⁸ complex samples per node and has a latency of 6 to 10 seconds. As the processing node continuously receives all sensing node data, geolocation points can be continuously produced with the aforementioned latency.

In order to achieve greater sensitivity, the low-level processing is required to do overlapped cross-correlations of different sizes across all three combinations of sensing node data. These cross-correlations are then mode filtered, multipath-filtered, parabolically interpolated, and given a quality metric.

Cross-correlation qualities that are greater than a predefined threshold are then fed into the Bancroft geolocation algorithm, which enable one to obtain a direct solution of the receiver position and the clock offset without requesting any a priori knowledge for the receiver location. The geolocation results can then be enhanced by an optional snap to the road filter. We will provide details of these steps in the following sections.

iGeoLoc_GPS Sensing Nodes. Each sensing node contains two software-defined radios and the necessary RF filters and amplifiers to perform the previously mentioned frequency translation for the data network. Each sensing node is controlled by a small micro-processing computer that controls and configures both the radios and a camera attached to a panoramic lens. A panoramic photo is taken once a second, providing context to the geolocation results. The computer communicates on the Wi-Fi control network. The component cost of a sensing node is approximately $5,000 CAD (about US$3,777). (See Figure 2)

iGeoLoc_GPS Processing Node. The processing node uses an appropriate RF antenna, filters and amplifiers to allow a software-defined radio with a custom field-programmable gate array (FPGA) design to receive the four sensing node backhaul bands and digitally down-convert them synchronously to baseband. The previously described processing chain (cross-correlation through geolocation) is then performed. The component cost of the processing node was approximately $20,000 CAD (about US$15,108), which can be reduced by using a low-cost alternative to a server-class computer for signal processing.

Reference Frequency – 27 Megahertz. The sensing nodes’ radios have RF local oscillators (LOs) that can drift relative to each other unless provided with a common reference. To avoid this, the processing node generates and transmits a continuous one-watt constant 27-megahertz tone as the reference signal. The 27-megahertz tone is in an industrial, scientific, and medical (ISM) RF band and in the range of the radios’ acceptable reference phase locked loop (PLL) frequency (5 to 104 megahertz). The implementation of this reference scheme encountered standard HF difficulties, of large antenna dimensions and high RF power.

Cross-Correlation Processing. Traditionally TDOA is performed by calculating the difference of arrival between two signals with absolute timestamps. Since a difference is a relative measure, it does not need to be derived from two absolute measurements; the difference can be obtained from a cross-correlation process with a known relative offset between the two signals. A calibration process (described later) ensures that the offsets in a set of node-pair differences form a consistent set of equations for computing the jammer’s location.

The cross-correlations are performed using 262,144 complex samples. With a bandwidth of five megahertz, a stationary assumption can be used for a source travelling at highway speeds. An overlapped method that varies the data block size by multiples of 8,192 complex samples was created to generate more cross-correlation results over the dataset that could then be used for the mode filtering (described later).

The five-megahertz sensing bandwidth also allows for cross-correlation peak determination with a resolution of 200 nanoseconds (59.95 meters). Figure 3 shows an example cross-correlation result.

Multipath Mitigation. CRC developed a cross-correlation quality metric to ensure that only reliable data is used for locating the jammer. The metric is defined to be the magnitude difference between the highest and second-highest cross-correlation peaks in the cross-correlation function.

To illustrate the need for this metric, Figure 4 shows how multiple cross-correlation peaks can result from multipath effects. These can sometimes be discerned based on having longer delays than the true signal, but this is not always possible. The peaks considered were above a noise level where the noise level is defined as the first peak, sorted in descending order (by magnitude), that is at most two-thirds the amplitude of the next-highest peak.

The system considered a maximum of two peaks and took the peak with the least delay; otherwise the cross-correlation was not used. Finally, a parabolic interpolation between samples was done to provide accuracies better than the 59.95- meter resolution mentioned earlier.

Mode Filtering. Low-level data processing involves mode filtering. In order to distinguish it from noise, a true crosscorrelation peak should be consistent through a great majority of all the overlapped cross-correlations in the dataset. The geolocation algorithm only uses cross-correlations with a mode value greater than 70 percent occurrence.

Calibration of Sensing Node’s Local Oscillators. The 27-megahertz common reference frequency locks (synchronizes) all the sensing nodes; however, it will arrive at the nodes at different phases. The phase difference between nodes will be a constant error. The system can calibrate out any constant errors as the TDOA technique is based on a difference in time that is relative. The calibration stage produces an offset for each combination of node pairs that compensates for all constant errors. A recalibration is required every time the radios’ LO changes, which is on reconfiguration, restart or reboot.

A linear system of equations is empirically obtained by transmitting white noise in the translated-jammer band, from one node at a time and cross correlating the receiving nodes to get the corresponding delay. This noise is generated by a pseudorandom bit sequence (PRBS) in the software-define radios of the sensing nodes. A minimum of three node pairs are required to be determined empirically, and the others can be solved analytically.

Geolocation Algorithm. The geolocation is accomplished using Bancroft’s Algorithm to solve the multilateration equations. However, this can result in multiple solutions due to the multiple points of intersecting hyperbolas, an example of which is shown in Figure 5.

A simple clustering algorithm is used to determine the best points. The clustering criterion is the number of neighbors within a pre-defined threshold distance. The remaining points can also be displayed, as shown in Figure 6. The clustering is only meant to aid a system operator and suffices for a stationary jammer, as the best points should be close together. However, if the jammer is believed to be mobile, a snap-to-road filter can be employed.

The snap-to-road filter uses the OSRM (open source routing machine) project. Offline maps are generated for use with the OSRM algorithm, which uses a Hidden Markov Model as the probabilistic approach in determining route feasibilities. “No U-turns” is the only constraint used with the OSRM routing algorithm. Figure 7 shows the estimated jammer position after applying the snap-to-road filter.

Geolocation to Google Earth – Testbed Visualization
In order to visualize the system, the processing node creates keyhole markup language (KML) files that describe the translated-jammer’s position and the generated geolocation point(s). These KML files along with the sensor nodes’ photos are sent over a one-kilometer Wi-Fi link to an office computer to display the results in Google Earth in near real-time (Figure 8 and Figure 9).

Interference Geolocation – iGeoLoc_GPS Results
Parameters and results from recent experimentation performed at the CRC Testbed for the geolocation were as follows:

iGeoLoc_GPS (interference geolocation)

• Tracked route of a mobile 200-milliwatt GPS jammer
• Four sensing nodes covering a 450×300–meter track 
• ~10second latency, with a 0–20-meter error

These excellent performance results led to some further validation tests outside of the CRC testbed, where we expected very poor performance due to the large network size and poor measurement geometry and obstructed propagation paths. The results were as follows:

iGeoLoc_GPS Range

• Tracked approximate position of mobile 1,200-milliwatt GPS jammer
• Some detections were 1.4 kilometers away (Figure 10) 

Jammer Situational Awareness – (jAware_GPS) Results
The results for the situational awareness are:

• jAware_GPS (jammer situational awareness) 
• detected only disruptive GPS jammers up to 200–250 meters away at highway speeds 
• one-second delay, measured actual GPS outage time

To validate the previously described translated jammer testbed, jAware_GPS was brought to a site along the highway in Ottawa where illegal GPS jammers were initially found in 2011. The jAware_GPS sensor was used to trigger a low-cost spectrum recorder, with a multi-second ring buffer, upon jammer detection. A post-processing algorithm found some chirp jammers in the triggered spectrum collection. However, other unknown events were detected that resulted in similar GPS outage periods, as were caused by the identified GPS jammers. Further investigation is warranted and is being undertaken. Figure 12 illustrates a correlation amplitude of a jAware_GPS-detected chirp jammer event and can be contrasted against Figure 11 where no jammer is present.

A GPS status report across the country, similar to a weather report, could be generated by networking jAware_GPS sensors along major highways to report current and forecast future GPS status. If such a system were in place, a GPS outage could be seen moving along a highway, and an outage forecast could be generated for critical infrastructure (e.g., outage approaching airports).

Conclusions
This effort has proven that it is possible to build a low-cost system to detect and locate GNSS jammers in near-real time. In just more than one year CRC has designed, built, and tested such a system using many novel and sophisticated techniques to achieve impressive results. The iGeoLoc_GPS and jAware_GPS systems are new tools that can protect GNSS from the perils of jammers. The GNSS community can now employ these tools, empowering its spectral awareness.

Acknowledgement
The author would like to thank the dedicated team members — Wayne Brett, Dr. Paul Guinand, and Russell Matt—as well as the CRC for making this project a success. 

The post Is it possible to build a low-cost system to detect and locate a single GNSS jammer in near-real time? appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

For the GPS community that business, at least in the near term, will likely center on changes in federal leadership — with many key appointments, like a new Secretary of the Air Force, still to be determined. In addition — even at this early stage when new lawmakers are still trying to find their offices — there are issues and opportunities worth watching in emerging legislation.

Washington has seen a lot of transitions, so even amidst political controversy it’s generally business as usual.

For the GPS community that business, at least in the near term, will likely center on changes in federal leadership — with many key appointments, like a new Secretary of the Air Force, still to be determined. In addition — even at this early stage when new lawmakers are still trying to find their offices — there are issues and opportunities worth watching in emerging legislation.

As the year kicks off the federal budget and the new administration’s spending plans are sure to be leading concerns for policy insiders. The government is roughly 90 days away from having to pass, finally, its fiscal year 2017 budget. The CR or continuing resolution — the short-term funding bill passed last year to keep the government from shutting down — expires at the end of April.

One of the goals of passing the CR at the end of last year was to give the incoming Trump administration an opportunity to impact the fiscal year 2017 budget. It is not clear how much Trump officials will be able to tweak the FY17 budget, but Donald Trump has said he wants to do away with defense spending caps imposed by the Budget Control Act and to expand the military. His nominee for Secretary of Defense, retired U.S. Marine Corps General James Mattis, made it clear during his Senate confirmation hearing that he’d like to see Congress repeal the Act and its budget-strangling sequestration requirement and give the military more money to address growing demands on its resources.

During the January 12 hearing there appeared to be broad support for more military spending including from the Sen. John McCain, R-Arizona.

“The President-elect has said he wants to ‘fully eliminate the defense sequester’ and ‘rebuild our military.’ If so, he will find many allies on this Committee,” McCain wrote in his opening remarks. “The Budget Control Act is harming us in ways that our enemies could only dream. We must repeal this legislation and increase the defense topline. This will not be cheap, but it pales in comparison to the cost of failing to deter a war, or worse, losing one.”

Not everyone in Congress is open to more spending, however, and one of the most strident budget cutters has now been nominated to oversee the federal purse.

Republican Rep. Mick Mulvaney, R-South Carolina, who Trump tapped as his budget director, has a record of fiercely supporting deep budget cuts and opposing efforts to raise the government’s debt limit. He has questioned the Pentagon’s approach to acquisitions and is one of the founders of the House Freedom Caucus, a group of conservative lawmakers whose budget stance helped pushed Speaker John Boehner (R-Ohio) to resign.

Not only will any increases in DoD spending have to get past Mulvaney’s budget-hawk colleagues, they will be jockeying for funds in the midst of a scramble to both cut taxes and create jobs through infrastructure spending. Moreover, Congress will have to approve raising America’s debt ceiling in the next several months, an issue that has proved highly controversial in the past, even within the Republican Party.

Waiting
In the meantime, some elements of the GPS program are on hold. Specifically, there is unlikely to be another GPS III launch contract announcement until after the fiscal dust settles.

“We may not be able to award the contract while we’re under a CR,” said an Air Force spokesperson.

“I’m going to wait until we see the law come out. You’ve seen the marks that have been out in the language that’s there. We’ll look at how that plays with what we’ve got,” said Lt. Gen. Arnold Bunch, the military deputy in the Office of the Assistant Secretary of the Air Force for Acquisition. He spoke with reporters January 6 after an Air Force Association (AFA) breakfast.

The budget is not the only factor, said Bunch, who noted that they are working their way through the contract source selection process, but they want to see what happens with Congress.

“Hopefully when that language comes out — we’ll get everything finalized — we’ll already be ready to award the contract,” said Bunch.

The Air Force may be waiting still longer for its new GPS ground system through program progressing, said Air Force Secretary Deborah Lee James, who addressed the same AFA breakfast — but the program is not “out of the woods yet.”

A Deep Dive review held January 5 showed that progress had been made, said James, in part due to the contributions of the new, computer-savvy Air Force Digital Service. “I’m confident that it’s going to be continuing to make that progress; I’m just not as confident on the time frame that’s going to be required,.” she said.

Indeed, some delay has already occurred, said DoD spokesman Mark Wright, who confirmed in a prepared statement that there might be further schedule slippage.

Undersecretary of Defense for Acquisition, Technology and Logistics, Frank Kendall, and the Air Force’s Service Acquisition Executive, Darlene Costello, conducted the fourth of a series of quarterly program reviews at the Raytheon campus in Aurora, Colorado, Wright he said.

“Raytheon briefed their progress on several topics,” Wright said. “Agile software development implementation is continuing with significant progress in developing cloud development environments. On Block 0, Raytheon completed the Launch and Checkout System Factory Qualification Test Runs for Record with an 88.6% pass rate, slightly higher than government expectation. Also, Block 1 software development recently delivered the latest iteration to testing with more Functional Objectives completed than planned.”

“Although some schedule slip to the targeted re-plan has occurred and more is not unlikely,” Wright said, “Undersecretary Kendall and Ms. Costello concluded Raytheon has made progress implementing these critical changes.”

What that means for the future is hard to predict. Trump has made it clear that he is unhappy with contracts that run over their budgets and schedules and he has taken public shots at some programs including the F-35 strike fighter jet. Raytheon’s OCX contract already faced cancellation this summer because of cost overruns and delays. The Air Force, however, has made it clear that it needs OCX. The selection of the new Secretary of the Air Force may provide a clue to the contract’s future.

Spectrum Proposals
Over on Capitol Hill, among the hundreds of bills already under consideration, is the MOBILE NOW Act (S. 19). Reintroduced by Sen. John Thune, R-S.D., after it failed to gain traction last year, the bill would mandate that 500 MHz megahertz of federal and nonfederal spectrum be found by the end of 2020 to support wireless broadband; of that 255 megahertzMHz must be below 6,000 megahertz.

This echoes the spectrum mandate issued by President Barack Obama in June 2010. That triggered a federal spectrum hunt that became an element in a 2011 fight between the GPS community and LightSquared (the firm has since changed its name to Ligado Networks) to rezone frequencies close to those used for GPS signals. Tests at the time showed that the firm’s network would overpower the vast majority of GPS receivers.

Ligado’s proposal has since been updated somewhat in terms of both the frequencies the firm wants to use and its proposed operational power levels. Even so the plan remains in limbo and concerns continue as new test results are released.

The MOBILE NOW Act takes four blocks of frequencies in the L band off the table when it comes to meeting the 500 megahertzMHz quota. The frequencies supporting GPS, however, are not in those protected bands.

The bill does say, the Secretary of Commerce and the Federal Communications Commission (FCC) must consider “the need to preserve critical existing and planned Federal Government capabilities.” It also notes “the need for appropriate enforcement mechanisms and authorities.” One of the concerns expressed regarding Ligado’s proposal is how interference would be monitored and addressed should a way forward be found.

The Ligado proposal is certainly not the first that raised worries about interference with the GPS signal and it is unlikely to be the last. Spectrum is valuable and lawmakers have long sought ways to free more frequencies for commercial use.

Thune has said, according to a report by Morning Consult, that he intends a step-by-step rewrite of the Communications Act of 1934. He would have allies on the House side in Reps. Greg Walden, R-Oregon and Rep. Fred Upton, R-Michigan, who began working in 2013 to recast the Communications Act. Among the ideas floated by Walden and Upton were flexible-use frequency licenses which, a white paper they issued said, would “permit licensees to use their spectrum for any service, including wireless, broadcast, or satellite services,” as opposed to the current system of designating what uses can be made of specific frequencies.

The GPS Innovation Alliance said at the time that “flexible use” was described in a separate white paper by the FCC Technical Advisory Committee (TAC) as permitting “uses up to and including high power mobile network downlinks.” This could cause interference to adjacent spectrum users who would be forced to accommodate, over time, their ill-located neighbors, the group said.

Walden and Upton fielded other ideas including setting receiver standards and downgrading the role of the National Telecommunications and Information Administration (NTIA). NTIA manages the federal use of spectrum and is an empowered, potential advocate for GPS.

Walden, who was just named chairman of the House Committee on Energy and Commerce, has already introduced one bill changing the Communications Act — but it has nothing to do with spectrum or the issues mentioned above. It proposes to change the way the FCC does its business to improve transparency and efficiency.

On a separate note, Sen. Deb Fischer, R-Neb. — along with Cory Booker DNew Jersey; Cory Gardner, R-Colorado; and Brian Schatz, D-Hawaii — introduced the Developing and Growing the Internet of Things (DIGIT) Act (S. 88). This bill, whose language had not yet been released as of press time, would direct the FCC to begin finding spectrum to support the Internet of Things.

PNT and Cybersecurity
While the spectrum-related bills could pose challenges to future GPS users, legislation seeking to protect the nation’s infrastructure and enhance cybersecurity could help protect systems that depend on GPS to function — and perhaps, by extension, GPS itself.

The Support for Rapid Innovation Act of 2017 (HR 239) would direct the Department of Homeland Security (DHS) — which already has the lead role in providing a backup for the GPS system — to support cybersecurity technologies. If passed, this would include, for example, activities such as developing and deploying more secure information systems and improving and creating mitigation and resilient networks. The bill would also direct DHS to assist in the development and support of technologies to reduce vulnerabilities in industrial control systems.

DHS has already determined that the data in the GPS signal is an essential element in 13 of its 16 critical infrastructure areas, going so far as to call it a “single point of failure for critical infrastructure.” Viewing PNT — additionally — as an essential part of cybersecurity, especially given the current political atmosphere, could open new avenues to securing a backup for PNT services.

“Accurate position, navigation and timing (PNT) is necessary for the functioning of many critical infrastructure sectors,” the agency wrote on its website. “Precision timing is one aspect that is particularly important, with one microsecond level or better synchronization often being required by numerous infrastructure systems, such as the electric grid, communication networks and financial institutions.”

GPS vulnerabilities are “absolutely” a cybersecurity issue, said Dana Goward, the president of the Resilient Navigation and Timing Foundation, which has been advocating for a GPS backup system. Disruption of the GPS signal, he said, “interferes with end use devices, it interferes with transmission pathways and it very much is capable of putting false data into databases. So yeah, it’s cyber every which way from Sunday.”

“GPS interference, whether intentional or unintentional, is a potential threat to multiple critical infrastructures,” said Scott Pace, a GPS expert and the director of the Space Policy Institute at the Elliott School of International Affairs at George Washington University. “While not commonly thought of as a cybersecurity issue, you can certainly make an argument that it should be.”

Moving Fast
The Support for Rapid Innovation Act, which was sponsored by Rep. John Ratcliffe, R-Texas, is moving through Congress at a fast clip. It has already passed the House and been assigned to the Senate Committee on Homeland Security and Governmental Affairs.

A sister bill, also sponsored by Ratcliffe, is on a similar trajectory. The Leveraging Emerging Technologies Act of 2017 (HR 240) would encourage DHS to engage with companies with innovative technologies that could address DHS needs. This bill seems focused on tapping entrepreneurial enclaves like Silicon Valley but also mentions incorporating “proven” technologies into an acquisition strategy.

Provisions in HR 240 could arguably encompass eLoran, a PNT backup system being tested by the Harris Corporation and UrsaNav in the United States and developed for use elsewhere in the world. Though DHS is already looking at eLoran, its approach has been fractured at best, with one part of the agency pondering ways to address GPS vulnerabilities while the Coast Guard, which has been part of DHS since 2003, was tearing down eLoran related infrastructure until it was finally ordered to stop by Congress. Being incorporated into a congressionally mandated, agency-wide plan to work with firms might be useful.

There are other bills of interest to the GPS community in the works. For example, the Weather Research and Forecasting Innovation Act of 2017 (HR 353) includes a provision ordering the National Oceanic and Atmospheric Administration to test an Observing System Simulation Experiment to assess the value of data from Global Navigation Satellite System Radio Occultation.

Like the two DHS bills, the weather bill has already passed the House and is in the hands of Senate lawmakers. It is not clear why these bills are moving so fast but perhaps it is a sign that Congress is poised for a productive year — a year that will, hopefully, move the marker on GPS issues.

The post GPS Roundup: Congress Reopens for Business appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Equations

Working Papers explore the technical and scientific themes that underpin GNSS programs and applications. This regular column is coordinated by Prof. Dr.-Ing. Günter Hein, head of Europe’s Galileo Operations and Evolution.

Working Papers explore the technical and scientific themes that underpin GNSS programs and applications. This regular column is coordinated by Prof. Dr.-Ing. Günter Hein, head of Europe’s Galileo Operations and Evolution.

Radio frequency interference (RFI) is a serious threat not only for users of satellite-based services, but also for the satellite-based systems themselves. The impacts of RFI at the user level range from temporarily affecting the quality of service of non-critical user applications over a limited or wide area (e.g., the quality at which some users are watching a football game) to affecting the quality of service of safety critical applications (e.g., avionics applications). At the system level, RFI can cause degradation in the quality of the satellite based services (i.e., increasing the demodulation error of uplinked data with temporary loss of a satellite’s availability) or even causing long-term service degradation.

The emission types can be categorized as intentional (jamming or spoofing) and unintentional. Nowadays, most of the RFI affecting satellite communication services is not intentional. (For an examination of satellite interference sources including those on GNSS signals, see the presentation by R. S. Jakhu listed in Additional Resources near the end of this article.) Unintentional interference cases are expected to increase in coming years with the constant increase of satellites in orbit, the congestion of already crowded frequency bands due to the new deployment of terrestrial and space systems, and the current trend in reducing equipment and installation cost (mainly in commercial systems). Moreover, intentional interference is increasing dramatically due to the availability of low-cost jamming devices on the market.

Different strategies can be adopted to handle interference, as shown by Figure 1:

• monitoring: monitoring emission over an identified frequency range;
• detection: detecting the presence of interference that can degrade the system performance; 
• characterization and classification: estimation of the main characteristics of the interfering signals, including the classification of the interfering signals within pre-defined classes of signals; 
• mitigation: all steps to counteract the interfering signal, e.g., interference nulling; 
• location measurements: extraction of location-dependent measurements from the interfering signals;
• localization: locating the interference sources via location algorithms that find these sources by processing the location measurements.

Localizing the source of RFI is becoming a priority in today’s satellite industry. Indeed, although much effort has been placed at the user level to design interference mitigation schemes to increase the system’s robustness in the presence of RFI on downlink signals, little has been done at the satellite level (i.e., on the uplink communication channel between a ground station and a satellite), whose local vulnerability propagates as a vulnerability in the entire system.

In this context, interference mitigation schemes can be useful to improve the performance of the system in the presence of RFI, but they cannot deter such type of threats from appearing in the future. Instead, interference localization provides the required essential information to the authorities on the location of the RFI source and time of such interference events, enabling them to stop the interference and prevent it from recurring.

This article continues a discussion begun in the Working Papers column in the November/December 2016 issue of Inside GNSS that addressed the theoretical background of interference localization. The current article focuses on the application of the techniques presented in that article to localize an interference source exploiting ground-based or space-based architectures.

Interference on Downlink Signals
The degradation of satellite downlink signals by means of interference directed to on-ground equipment is a well-known issue that must be taken into account in the receiver design. In this scenario, the interference signal arrives at the antenna elements of on-ground devices (e.g., user equipment) with a power and band such that it can affect the reception of downlink communications addressed to those devices. This type of interferer usually affects only a few devices in a limited area; nonetheless, this area could include critical infrastructure such as an airport.

Historically, intentional interferers are common for military scenarios. However, due to the availability of low-cost jamming devices on the market, intentional interference of civil applications is becoming common as well, although most remains unintentional. The latter interference stems from the large number of communication systems present in our daily life that emit out-of-band power interfering with satellite communications. For example, for the GNSS L-band the nominal on-ground received power is about –160 dBW. Despite the weakness of the signal, the spread spectrum nature of GNSS signals allows navigation receivers to recover timing information and to estimate the pseudoranges necessary to compute the user position by exploiting the gain obtained at the output of the correlation block.

Even if the correlation process is theoretically able to mitigate the presence of nuisances in the bandwidth of interest, a real limitation can be the finite dynamic range of the receiver front-end. The presence of undesired RFI and other channel impairments can result in degraded navigation accuracy or, in severe cases, in a complete loss of signal tracking.

Interference on downlink signals can be detected and localized by exploiting either a ground based architecture (in which on-ground sensors are spread in the area that must be monitored), or a space based architecture (in which a single satellite or multiple satellites are employed to monitor large areas). In both cases, the (on-ground or on-space) sensors must listen for the presence of RFI in the bands of interest, and jointly process the received RFI in order to localize and track the interference sources.

Interference on Uplink Signals
In this scenario the interference signal arrives at a satellite antenna element with a power and band such that it can affect the reception of uplink communications addressed to the satellite. This type of interferer may have a large effect satellite services over a wide area. For example, for a GNSS satellite the interferer may affect either:

• the upload of the navigation and integrity data (mission uplink), which are subsequently broadcast through the navigation signals to the users: this may cause the degradation of the positioning and timing accuracy over the whole area covered by that satellite;
• the telemetry, tracking, and command (TT&C) communication, through which a satellite is controlled and operated: this may cause a (temporary or even permanent) satellite outage, resulting in the degradation of the GNSS service availability and performance.

RFI also represents a serious threat for the SATCOM satellite communications (satcom) industry. Although only a small amount of satellite capacity is affected at any time by interference, 85–90 percent of satcom customer issues are related to RFI. The majority of interference cases still come down to human error or equipment failure; intentional interference counts for less than five percent of interference cases, but this percentage is increasing dramatically over time.

Interference on uplink signals can be detected and localized through a space-based architecture, in which a single satellite or multiple satellites are employed to monitor large areas, which can also be incorporating on ground equipment for the processing of the collected samples from space and the calibration of the on-board the spacecraft equipment. Various solutions have been developed to enable satellite owners and operators to detect and localize RFI sources. Many of these solutions are based on a multi-satellite architecture, in which the signals received by multiple satellites are forwarded to and analyzed by ground equipment.

The main disadvantage of a multi-satellite solution is that it requires at least two satellites that are in close proximity to each other and that have the same uplink frequency ranges, polarization, and footprint coverage. Moreover, such systems require information such as the exact positions and velocities of both satellites. Because of these limitations, single- satellite solutions have recently been investigated and developed, which are discussed in several items in the Additional Resources section. Single-satellite solutions are in general more challenging in terms of design complexity and achievable localization accuracies.

Ground-Based Architecture
GNSSs are nowadays supporting many safety-critical applications (e.g., civil aviation and maritime) and liability-critical applications (e.g., financial transaction time-stamping). The correct operation of GNSS requires that each segment (user, space, and ground) of the system fulfills certain requirements in terms of availability, continuity, and accuracy. In particular, the ground segment is used to:

• monitor navigation signal quality (monitoring stations);
• upload the navigation message adjustments (uplink stations); and, 
• operate the spacecrafts’ fleet trough Telemetry Tracking & Control (TT&C).

GNSS ground stations are a vulnerable entry point for the overall service availability. GNSS systems heavily rely on redundancy to minimize the single-point of failure effect, but it is clear that the impact of a potential attack to ground stations, even if very unlikely, is very high.

Many of the coauthors of this article are actively involved in the European Commission FP7 PROGRESS project, which is focused on improving the security and resilience of GNSSs by protecting ground infrastructures.

The PROGRESS project, after a preliminary risk assessment phase, develops detection, location, and mitigation strategies against the most harmful attacks to GNSS ground stations, for example:

• ground facility physical attacks, including explosive attacks and highpower microwave attacks
• RF spoofing and jamming 
• cyber-attacks.

One of the three subsystems developed within the PROGRESS frame is an Interference Detection and Localization System (IDLS). The IDLS primarily targets intentional interference rather than unintentional interference sources, and, in particular:

GNSS Jamming. This threat can cause denial of service (DoS) of GNSS receivers used in the GNSS ground infrastructure. A review of some simplistic and medium-advanced COTS jammers is given in the article by R. Bauernfeind and B. Eissfeller listed in Additional Resources.

GNSS Spoofing. This threat involves the transmission of signals originating from an adversary source that would appear as legitimate to the end-user receiver although they would convey misleading information into GNSS receivers. It may cause deception of service, because the receiver may lock onto the malicious signal instead of following the authentic one. Spoofing signals can also cause a denial of services when they impose a C/N₀ degradation to the receiver correlation process.

IDLS focuses on the protection of the downlink navigation signal received by GNSS receivers embedded in GNSS ground stations and subsequently used for monitoring or time calculation purposes. The navigation signal is in fact very weak and in many cases reaches the front-end input with a power 20 decibels lower than the noise floor. The detection and localization solutions developed in IDLS can easily be extended to cover other bands of interest.

IDLS Architecture
IDLS design is based on several environmental and geometric assumptions for sensor stations or mission control centers:

• Sites are located in rural or periurban environments. Sites are always protected by a fence, whose area is at least 100×100 meters for monitoring stations and 300×300 meters for mission control centers.
• GNSS receivers use hemispherical reception antennas, positioned in open sky visibility, on buildings surrounding fields or on building roof tops. They are mounted on a mast of approximately one to two meters height and the distance from the site fence is not specified (even though it is typically 30 meters). GNSS receivers use the omnidirectional receiver L-band antenna connected with a coaxial cable length of up to 100 meters. 
• The coverage area, i.e., the area monitored by the IDLS, is a circle with the target victim receiver in the center and a radius of at least two kilometers.

On the other hand, some assumptions regarding the attacker must also be considered in the design of the system:

Attacker position. The IDLS system is mainly able to localize on a two-dimensional (2D) plane, as further described in the following part of this section. A 3D localization is practically unfeasible with 2D sensor placement. All the scenarios considered target detection and location of ground-based emitters, such as car jammers or hand-held jammers that can be easily hidden in the environment outside the fence of any GNSS ground infrastructure. Even unmanned air vehicle (UAV) -mounted interferers can be partially localized in the 2D plane. It is also assumed that the attacker is able to estimate the distance from the target victim device.

Attacker velocity. A stationary or slowly moving attacker is assumed. For spoofing attacks, the relative motion induces a doppler effect that must be compensated by the attacker so it is assumed that a stationary attacker is a more realistic scenario. Dynamic scenarios are realistic for jamming attacks and can be tested as well.

Attacker appliance. The attacker is assumed to be able to estimate the distance from the target victim device with laser distance estimation tools providing one-meter accuracy. The attacker is also assumed to have sufficient energy storage (batteries or compact electrical generators) to sustain any jamming or spoofing attacks.

In the case of UAVs, only professional grade devices can provide energy and carry the weight of all appliances. For both jamming and spoofing attacks, SDR signal generators are envisaged, given their high flexibility. A compact, lightweight, helix RHCP (right hand circularly polarized) antenna is assumed because it maximizes the power coupling for a given emitted power (the target antenna is also RHCP). Given the receiving pattern (hemisphere) for the “victim” GNSS RX receiver antenna, the relative altitude ΔH (<10 meters), and the relative distance ΔD (e.g., 500 meters), the angle is roughly one degree; so, the relative power loss due to pattern coupling is minimized (a maximum of three to five decibels), as sketched in Figure 2.

Each IDLS node is composed of a cluster of networked equipment intended to detect and localize jammer and spoofer activities and notify the Security Control Center (SCC), as illustrated in Figure 3. The SCC collects and processes IDLS and other detection and location subsystems developed in the PROGRESS framework. All the interfaces among IDLS components as well as between the IDLS and SCC are based on HTTP+JSON for the ease of integration and for higher flexibility.

Each IDLS node comprises:

• one IDLS controller that is the star-center, collecting data from all peripheral sensors and performing the location computation
• a number of IDLS sensors, sensing the environment around the receiver being protected 
• one IDLS gateway, used to collect controller data and provide them to the SCC. IDLS has been designed as a cluster of networked sensors with a single-input frontend for the following reasons: 
• to provide an even detection capability in the coverage area, i.e., the area surrounding the fence 
• to provide a degree of redundancy in the detection network; In practice the only weak point is the central controller, which logically implements the star topology. This device is intended to be installed in a controlled environment and to implement physical redundancy countermeasures to increase availability and robustness against attacks. 
• to provide an affordable and scalable architecture. The use of a simple single-antenna front-end lowers the sensor CAPEX (cost of sensor purchase) and OPEX (sensor calibration and maintenance costs), with respect to complex multiple-input frontends.

This infrastructure can be coupled with a localization algorithm based on time difference of arrival (TDoA) measurements. The essential requirement is that the sensors must acquire signal batches in a synchronous manner; in fact, a synchronization error of less than 100 nanoseconds is required to provide good accuracies. This requirement induces a proper architecture for synchronization distribution and a data network used to forward batches to the central controller for localization purposes.

PPS (pulse per second) signals can be generated in the central controller and distributed with a coaxial cable or a fiber optic cable (relative synchronization). An alternative is to use an absolute PPS generation in each sensor (absolute synchronization), coupling a commercial off-the-shelf (COTS) GNSS receiver with a precise clock (disciplined oscillator).

In the case of jamming or spoofing detection, the oscillator shall be put in hold-over mode to continue generating a valid PPS signal, while in the case of no-interference, the GNSS receiver shall compensate for oscillator drifts. This implementation is still under investigation for future uses because it links the PPS quality to the detection capabilities, thus increasing the complexity of the system.

All the sensors, in a practical installation, will be arranged in the same plane, with minimal variability in height. This placement allows for a good 2D localization, if the sensors are properly arranged, but a very poor 3D localization, due to the absence of height diversity.

For a 2D location at least three sensors must be used. However, an additional sensor is positioned near the target victim receiver to improve the detection capabilities near the target receiver and the quality of the location results. Hence, in the final configuration four sensors are used, as sketched in Figure 4.

The sensors’ placement can have a severe impact on overall performance of the location algorithm. The best accuracy with TDoA can be obtained with the sensors positioned at the coverage area limits, i.e., several kilometers apart. However, this configuration is not practical as it increases the cabling capital (CAPEX) and operational (OPEX) expenditures, and does not allow for protection of the sensors. It is, in fact, desirable to have all the sensing devices in a protected zone, i.e., within the ground infrastructure’s fence. Therefore, a good compromise is to arrange the IDLS sensors near the fence, 150 meters apart from each other, as illustrated in Figure 4.

The article by Y.-P. Lei et alia cited in Additional Resources describes the optimal disposition of a set of four sensors. In Figure 5 three configurations are analyzed by simulation. The geometric dilution of precision (GDOP) is plotted with respect to the interferer position. The proposed Y-shaped disposition provides the fairest results when the location of the interference is not known, resulting in the maximal flatness of GDOP.

Case Study: Spoofing Localization
Using the state of the detection algorithms available in the technical literature, Qascom has developed a highly optimized detection core capable of fusing the outputs of different algorithms. IDLS sensors are embedded with raw data acquisition frontends, plus a GNSS COTS receiver that outputs observables data.

Jamming detection is based mainly on processing of raw data batches because observables-based detection is less sensitive (as discussed in the publications by L. M. Marti and B. Motella et alia in Additional Resources). In contrast, spoofing detection employs techniques based on both pre-correlation methods and observables checks (described in the papers by S. Fantinato et alia and A. Jovanovic et alia). The use of raw data batches allows for an increase in sensitivity with respect to simple checks of observables and allows for the use of TDoA for both jamming and spoofing location.

The jamming location uses classical TDoA algorithms. The localization is performed in the central controller upon reception of raw batches:

• raw measurements calculation: extrapolate the delay and doppler error of the sensor i with respect to the reference sensor, using the cross ambiguity function (CAF). Only delay measures are used for TDoA.
• localization: perform the Least Square estimation directly in the central controller.

In this section a particular case study is described: spoofing location. As described in the paper by A. Broumandan et alia, a network of COTS receivers is used to estimate carrier phase double difference and hence the position of the spoofer. The novel IDLS approach instead follows the modified TDoA approach described in the paper by G. Gamba et alia. Classical TDoA directly using the CAF generally gives poor results. Cross correlation of signals containing different PRNs (PseudoRandom Noise sequences associated with each satellite) results in a linear combination of incoherent peaks, with different delay, Doppler, and phases.

In fact, as Figure 6 shows, the received signal for sensor i is composed of several components for each satellite j, both authentic signals S_i,j, and spoofing ones I_i,j:

Equation (1) (for equations, see inset photo, above right)

An authentic signal depends on the position of the sensor x_i, whereas a spoofing signal depends on both x_i and x_rx, the position of the victim receiver.

A preliminary “projection” in the PRN subspace is used to improve the sensitivity and accuracy of the location. The raw batches are correlated with each PRN locally in each sensor. This correlation step is performed using synchronized local replicas in each sensor, providing a common time-base for all the sensors in the cluster. This method allows performance of the delay estimation on a per-satellite basis.

Sensor 1 and Sensor 2 can project the signal on PRN_j:

Equation (2)

Equation (3)

The values τ₂ – τ₁ calculated on the same time-base (since all sensors are synchronized) can be used to calculate the relative delay:

τ₂₁ = τ₂ – τ₁     (4)

In the case of a single spoofer, for a given PRN, the CAF can show a different number of peaks, derived by superposition of authentic and spoofing signals. If neither authentic nor spoofing PRN is present, the CAF will show no peaks.

The most difficult condition occurs during an attack. In the case of aligned attack, the delay, doppler, and power level are similar, and the peaks may merge. If only a single peak is detected, it is difficult to understand whether it is due to an authentic-only signal, to a spoofing-only signal, or to a mixture of aligned authentic and spoofing signals. When the attack is not aligned, as in meaconing attacks or after steady state has been reached, the peaks should be easily discriminated.

Figure 7 illustrates an example of a CAF of a simulated meaconing attack. Assuming two peaks for four sensors, a total of 16 combinations must be tested.

Figure 8 shows the results of a simulation of a possible layout around Qascom headquarters. The result on the left side shows a localization exploiting only the peaks associated with the spoofing signal. The measurements are very consistent, and this leads to a small localization error: the spoofer position (green label) is correctly estimated, with error bounds of a few tens of meters (see the 50-percent confidence ellipse).

The result on the right side of Figure 8 shows a TDoA-based localization that exploits only the CAF peaks associated with the authentic signal. In this case the measurements are not very consistent, and this leads to an apparent position near the center of the cluster, with an estimated error far above the previous case.

Figure 9 provides the residual cost of the multi-hypothesis test with each combination of four peaks (hence a total of 16 combinations). The normalized cost is inversely proportional to the likelihood that the given combination of peaks is coming from a ground-based emitter. The lower the cost, the higher the likelihood that the combination is consistent with a spoofer. The lowest cost solution is represented by the spoofer-only solution, while the second lowest is due to authentic peaks combination. Basically, 14 combinations do not converge to any position, because the cost is very high. The localization error confirms this trend.

The IDLS is in the final development stage. From preliminary assessments, the following performance is expected:

• jammer detection sensitivity down to -90 dBm (at the IDLS sensor antenna connector)
• jammer location accuracy (one jammer) down to 50 meters 
• spoofing detection sensitivity down to -3 decibels with respect to the authentic signal-in-space (SIS) 
• spoofer location accuracy (one spoofer) down to 50 meters.

Space-Based Architecture
A space-based architecture for interferer localization can be exploited to detect and localize different types of interferers. It is important to differentiate between the following two types of scenarios:

Interference on Downlink Signals. In this scenario, the interference signal arrives at the antenna elements of devices (e.g., user equipment) on the ground with a power and band such that it can affect the reception of downlink communications addressed to those devices. These types of interferers may be localized via dedicated satellites placed in low orbits. For example, a powerful interfering signal at 20 dBm (feasible even with low cost devices), transmitted with a nondirective antenna, might be detected from a low Earth orbit (LEO) satellite orbiting at an altitude of 700 kilometers.

Interference on Uplink Signals. In this scenario, the interference signal arrives at a satellite antenna element with a power and band such that it can affect the reception of uplink communications addressed to the satellite. These types of interferers may be localized by the satellite experiencing the interference (possibly in collaboration with other satellites) or by dedicated satellites placed in lower orbits whose goal is to monitor and localize the interference that may affect satellites placed in upper orbits.

Multiple antenna elements are helpful in order to generate the differential measurements (e.g., TDoA or frequency difference of arrival) or the angle-of-arrival (AoA) measurements adopting multi-antenna techniques (e.g., multiple signal classification [MUSIC] or amplitude comparison monopulse [ACM]). These antenna elements may be placed in the same satellite or in multiple satellites. Figure 10 shows an example of a single-satellite architecture (left side) and a two-satellite architecture (right side).

On the one hand, a multi-satellite architecture generally allows for much better performance than a single-satellite architecture, in particular if the signal received by multiple satellites is jointly processed. Indeed, two geometric benefits are associated with a multi-satellite architecture: 1) the farther apart the antenna elements generating a specific differential measurement are, the more stable the locus of points of that measurement with respect to measurement errors; 2) the further apart the sensors collecting different measurements are (e.g., AoA collected by two separated satellites instead of AoAs collected by two antenna arrays placed on the same satellite), the more stable the intersections of the loci of points of those measurements with respect to measurement errors.

Notice that the first advantage refers to the information carried by a single measurement and requires a joint processing of the signal received by different satellites, whereas the second advantage refers to the efficiency at which multiple measurements can be aggregated together to compute a position fix.

On the other hand, a multi-satellite architecture suffers from the drawback that the interference may not be visible by multiple satellites unless the satellites are in close proximity, but this would limit the performance benefits. Moreover, multi-satellite architectures are much more complex to implement because they require time and frequency synchronization among satellites, and they also require collecting the information (about the RFI signals and about the states of the satellite) in a common node.

This common node may be a specific satellite, in which case inter-satellite communication is required, or onground equipment to which the satellites forward the (possibly pre-processed) received signals. In the latter case, the capacity and availability of the downlink among the satellites and the on-ground equipment poses some constraints on the interference processing capabilities, which may result in performance degradation.

To study the impact of different architectures and localization techniques with respect to multiple interferer scenarios, we employed the Ground to Space Threat Simulator (GSTS), whose high-level design is shown in Figure 11. Such a simulator is divided into four main modules:

1. The Scenario Generation Tool (SGT) is responsible for the overall scenario configuration, it includes a graphic user interface to set the different parameters of the simulation.

2. The Raw Data Generator Emulator (RDGE) generates the results of the processing of the received signals, in particular the location-dependent measurements. It can do this in two modes, either in 1) simulative mode, by generating the transmitted signal (interference signals and possibly uplink signals), applying the channel effects, acquiring and processing the received signals; or in 2) analytic mode, which exploits the geometry of the scenario and statistic models that are pre-generated with the simulative mode in order to directly generate the location measurements.

3. The Geolocation Core (GC) is in charge of performing the localization at a pre-selected simulation rate using the location measurements that are provided by the RDGE.

4. The Localization Performance Analysis Tool (LPAT) compares the geolocalization results with the real data, and generates the desired figures of merit.

We will next discuss the localization results obtained with the GSTS tool for two case studies.

Case Study 1: Static Interferer, MEO Satellite
The first case study simulated the use of a static interferer transmitting a continuous wave interferer signal while employing a single MEO satellite with an antenna array of three elements and an ACM antenna with four feeders to localize the interference source. The simulation lasted two hours and during this time the signal-to-noise ratio (SNR) ranged from 10 decibels (when the satellite is farthest from the interferer) to 13 decibels (when the satellite is closest to the interferer).

Every second each satellite antenna collected a batch of 10 ms of the received interference signal. Through a joint processing of the collected batches the following location measurements are generated every second: three TDoA (one for each pair of the three antenna elements), one AoA obtained through the MUSIC algorithm, and one AoA obtained through the ACM algorithm. The article by L. Canzian et alia contains details on the generation of these measurement types and the information they carry.

We evaluated the two localization techniques discussed in the first part of this series (L. Canzian et alia): the Taylor-Series (TS) and the Extended Kalman Filter (EKF). TS is a batch technique that maintains in memory and exploits all measurements collected up to the current time instant to perform a localization calculation. To limit the storage and computational complexity requirements of the TS technique, the number of measurements to save and use must be bounded. For this reason, the number of measurements that were stored and exploited at a certain time instant were limited to all measurements collected during the previous hour. Instead, EKF is a sequential technique that processes each measurement once, as soon as it has been collected, in order to update an internal status that includes the current interferer position and velocity estimates, and the uncertainties associated to such estimates (i.e., the covariance matrixes).

Ideally, localizations should be performed whenever a new measurement is collected, i.e., every second. However, because the TS technique becomes computationally complex when many measurements are available (e.g., 10800 TDoA measurements are collected in one hour), and because the localization accuracies become quite stable after some tens of minutes, it has been decided to trigger localization at irregular time intervals: more often at the beginning (when results are less stable), and less frequently at the end of the simulation (when localizations are converging).

Figure 12 shows a 3D representation of the considered scenario, the yellow triangle in northwestern Africa represents the simulated interferer position, whereas the green line represents the trajectory of the satellite during the simulation, and the green plus sign (+) is, the final position of the satellite.

Figure 13 and Table 1 show the localization accuracies of different techniques for this first case study, defined as the average distance between the estimated and the actual interferer positions (average with respect to 100 simulations), for different time instants from the beginning of the simulation.

In general, for all techniques and measurement types, the localization accuracy improves over time, but a big difference appears between the performances associated with different measurement types for this first scenario:

• TDoA allows for an average accuracy on the order of 100 kilometers even after a long collection time;
• AoA (MUSIC) achieves average accuracies of a few kilometers after a short collection time interval due to the high precision at which MUSIC estimates the AoA. 
• AoA (ACM) is not as accurate as AoA (MUSIC) over a short time interval, but its performance improves quickly. Indeed, in the current scenario, the AoA estimated by ACM is not as precise as the one estimated by MUSIC at the beginning of the simulation, but it improves in time as the satellite nears the interferer zenith.

Comparing the results achieved by the TS technique with those obtained by the EKF technique, one can see that TS performs very poorly with respect to EKF when only a few measurements are available, in particular for TDoA and AoA (ACM) measurements that are less accurate than AoA (MUSIC) measurements. In fact, because the TS estimation is not constrained to stay on Earth’s surface, TS may suffer from convergence problems or may converge to a very distant location (e.g., close to the satellite position) when there are very few measurements. However, when many measurements are available, the performance of the TS becomes comparable or even better than that achievable by the EKF, in particular for very accurate measurements such as the AoA generated by MUSIC or ACM.

Case Study 2: Dynamic Interferer, MEO Satellite
The second case study considers a dynamic interferer moving at 100 km/h transmitting a continuous wave interferer signal. The same MEO satellite of the previous case study is employed, equipped with an antenna array of three elements and an ACM antenna with four feeders. The only difference with respect to the previous scenario, represented in Figure 12, is that now the interferer is traveling 100 km/h toward the east.

As in the previous case study, the evaluated localization techniques are TS and EKF, with the considered measurement types TDoA, AoA (MUSIC), and AoA (ACM).

In disagreement with the static case, the localization accuracy not always improves with time when evaluating a dynamic interferer, as reflected in Figure 14 and Table 2. This is particularly evident for the TS technique and for the measurements allowing for high accuracy, i.e., AoA (MUSIC) and AoA (ACM). As discussed earlier, such schemes converge to a very accurate interferer position estimate after a short collection time interval. However, because it is dynamic, the interferer moves away from such a position estimate; hence, the localization performance grows worse over time.

Concerning the EKF, we note that in the short term the results are very similar to those obtained for a static interferer, but in the long term they are worse. In fact, when the interferer is dynamic it takes a longer time to converge to the correct position of the interferer, tracking its trajectory.

The accuracy trend for the EKF technique can be divided into three phases: The accuracy initially rapidly improves (Phase 1), then slowly degrades (Phase 2), and finally improves again and converges to a value close to the real interferer position (Phase 3).

During Phase 1 localization accuracy is quite poor because few measurements are available; hence, additional measurements can significantly improve the localization accuracy.

During Phase 2 the performance tends to worsen slightly over time. Indeed, in this phase the velocity of the interference source is not estimated accurately because the considered EKF starts with an a priori state in which the average velocity of the interference source is 0 m/s and its standard deviation is 2 m/s, with respect to each axis. Because the initial velocity state is quite small with respect to the actual interferer velocity, EKF tends to converge to a point that minimizes the distance from all measurements collected so far (similar to the Taylor Series techniques). As time goes on, the interferer moves away from this point; hence, the geolocalization accuracy grows worse.

Finally, during Phase 3 the performance starts to improve again. Indeed, at the end of Phase 2 the EKF technique starts to improve the velocity estimation of the interferer source. As a consequence, the localization accuracy improves as well, up to a time at which both the position and velocity estimates converge to values that are very close to the real interferer position and velocity. Within the considered time horizon of two hours, EKF-TDoA does not enter Phase 3.

Conclusions and Future Work
This article discussed the practical aspects associated with single-interferer localization approaches. It described two different types of localization architectures, ground-based and space-based, and provided results of simulations showing the performance that such architectures can achieve in specific scenarios.

For the ground-based architecture, we discussed the performance of the IDLS module. Among the configurations of sensors that we considered, the Y-shaped disposition configuration is shown to be the one providing the maximal flatness of GDOP.

The simulation results of a possible layout around Qascom headquarters are discussed. These results show that the multi-hypothesis test, based on the residual costs for different peak combinations, allows for extraction of the correct peak combinations for the authentic signal and the spoofing signal. The latter can be used to achieve a very accurate localization of the spoofer.

For the space-based architecture we described the GSTS simulator, which enables us to study the performance of different space-based architectures and localization techniques with respect to multiple interferer scenarios.

We carried out two case studies, demonstrating that a single MEO satellite, exploiting multiple antennas to generate TDoA or AoA measurements, can be employed to locate a static interferer with an accuracy as low as a few kilometers after a collection time of some minutes. The tracking of a dynamic interferer moving at 100 km/h, on the other hand, requires longer collection time intervals.

It would be possible to show significantly better results if a LEO satellite were used in place of the MEO satellite, because the LEO would be much closer to the interferer source and would cover a much wider angular span than the MEO satellite during a specific time interval. For the same reason, the results would be significantly worse for a single GEO satellite. It is also possible to show that a multiple satellite architecture would allow for much more accurate localizations, although it suffers from many drawbacks described within this article.

Future research directions include the investigation of additional localization techniques, such as the use of a particle filter for single-interferer localization and multiple hypothesis tracking techniques for multi-interferer scenarios. These techniques have already been integrated within the GSTS simulator, and a preliminary analysis shows that they are capable of improving the localization performance for the single interferer scenario. However, this improvement comes at the cost of a more demanding technique, in terms of memory and computational complexity requirements.

Another important research direction includes the integration of ground and space systems for interference localization. Indeed, although they are designed for different applications and scenarios, the interference processing functions and the interfaces have several commonalities. These shared elements can be exploited to develop future systems in which ground and space systems cooperate to maximize their ability to locate interference sources.

Acknowledgments
GSTS has received funding from the European Space Agency (ESA) under Contract No. 4000113560/15/NL/HK. The project started on April 30, 2015 and was scheduled to be completed by the end of 2016.

PROGRESS has received funding from the European Union Seventh Framework Programme FP7/20072013 under grant agreement n° 607669. The project started on May 1, 2014 and is due to be completed by April 30, 2017.

The information appearing in this document has been prepared in good faith and represents the opinions of the authors. The authors are solely responsible for the content of this publication, which does not represent the opinions of the ESA and the European Commission. Neither the authors, nor the ESA, nor the European Commission are responsible for any use that might be made of the content appearing herein.

Additional Resources
[1] Bauernfeind, R., and B. Eissfeller, “Software- Defined Radio Based Roadside Jammer Detector: Architecture and Results,” Position, Location and Navigation Symposium – PLANS 2014, 2014 IEEE/ION , pp. 1293–1300, 2014
[2] Broumandan, A., and A. Jafarnia-Jahromi, S. Daneshmand, and G. Lachapelle, “A Networkbased GNSS Structural Interference Detection, Classification and Source Localization,” Proceedings of the ION GNSS+ 2015, Tampa, FL, 2015
[3] Canzian, L, and S. Ciccotost, S. Fantinato, A. Dalla Chiara, G. Gamba, O. Pozzobon, R. Ioannides, and M. Crisci, “Interference Localization from Space: Theoretical Background,” Inside GNSS, Volume: 11, Issue: 6, November/December 2016
[4] Canzian, L., S. Fantinato, S. Ciccotosto, O. Pozzobon, D. Petrolati, R. Ioannides, M. Crisci, “Software Tool for the Assessment of On-Board Satellite-Based Interference Geolocation Techniques”, in Proc. ESA Workshop on Advanced Flexible Telecom Payloads, Noordwijk, March 21-24, 2016.
[5] Coleman, M., “Satellite Interference – Issues of Concern,” Talk Satellite – EMEA, 23 June 2014.
[6] Fantinato, S., and S. Montagner, O. Pozzobon, and S. Ciccotosto, “Spoofing Monitoring Sensor for Critical Applications,” European Navigation Conference, Helsinki 2016
[7] Gamba, G., and A. Dalla Chiara, O. Pozzobon, and D. Serant, “PROGRESS Project: Jamming and Spoofing Detection and Localization System for Protection of GNSS Ground-Based Infrastructures,” Proceedings of ION GNSS+2016 Conference, Portland, OR, 2016
[8] GLOWLINK–Single Satellite Geolocation (SSG).
[9] Greilinger, E., “Beyond the Limits of Traditional Interference Mitigation Solutions,” SatMagazine, pp. 58–59, February 2016
[10] Jakhu, R. S., “Satellites: Unintentional and Intentional Interference,” presentation at Radio Frequency Interference and Space Sustainability panel discussion, Washington, D.C., June 2013
[11] Jovanovic, A., and C. Botteron, and P.-A. Farinè, “Multi-test Detection and Protection Algorithm Against Spoofing Attacks on GNSS Receivers,” Proceedings of ION PLANS, 2014
[12] Kaplan, E., and C. Hegarty, Understanding GPS – Principles and Applications, Artech House, 2005
[13] Lei, Y.-P., and F.-X. Gong, and Y.-Q. Ma, “Optimal Distribution for Four-Station TDOA Location System,” Biomedical Engineering and Informatics, 2010
[14] Marti, L. M., Global Positioning System Interference and Satellite Anomalous Event Monitor, Ph.D Thesis, Ohio University, 2004
[15] Motella, B., and M. Pini, and L. L. Presti, “GNSS Interference Detector Based on Chi- Square Goodness-of-Fit Test,” 6th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC), pp. 1-6, 2012
[16] Musumeci, L., “Advanced Signal Processing Techniques for Interference Removal in Satellite Navigation System,” Ph.d thesis, Politecnico di Torino, 2014
[17] SIECAMS – Satellite Monitoring and Geolocation System.

The post Interference Localization from Space, Part 2 appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

The Indian Regional Navigation Satellite System (IRNSS) became fully operational in May 2016 with the operational name of NavIC (Navigation with Indian Constellation). The system consists of three geostationary orbit (GEO) satellites and four inclined geosynchronous orbit (IGSO) satellites (see Table 1, inset photo, above right). IRNSS has been developed by the Indian Space Research Organization (ISRO) with the objective of offering positioning, navigation and timing (PNT) to the users in its service area. The IRNSS satellites transmit navigation signals on frequency L5 (1176.45 MHz) which is shared by three other GNSSs, i.e., GPS, Galileo and the Quasi-Zenith Satellite System (QZSS), making the IRNSS interoperable with those systems.

All the satellites belonging to the latest generation of GPS, called Block IIF, have been sending out the L5 signal since 2010 as part of the GPS modernization.

With the launch of the last satellite of Block IIF on February 2016, it now has all its 12 satellites operational. The next generation of GPS satellites, GPS III, will also transmit the L5 signal. GPS III is planned to become fully operational with a constellation of 32 satellites by 2025, and the first launch thereof is now expected in spring of 2018.

In this article, we provide the very first empirical and formal L5 ambiguity resolution and corresponding positioning results of the fully operational IRNSS as a standalone system and also in combination with the fully operational GPS Block IIF. For several onshore locations within the IRNSS service area (Figure 1), we investigated the potential of single-frequency (L5) single-epoch real-time kinematic (RTK) positioning. This is carried out for different underlying models, including standalone IRNSS, IRNSS+GPS Block IIF, standalone GPS III and IRNSS+GPS III. With the emergence of low-cost single-frequency RTK receivers and their mass-market applications, our analysis is done for geodetic survey-grade receivers as well as low-cost receivers.

Measurement Experiment
We based our analyses on the IRNSS L5 and GPS L5 data-set recorded by two GNSS receivers of a short baseline between the receiver pair (CUBBCUCC) at Curtin University, Perth, Australia. Figure 2 shows the observed carrier-to-noise densities (C/N₀) of IRNSS and GPS L5-signal.

As the GPS L5 signal has larger C/N₀ values compared to the IRNSS L5, its precision is expected to be higher with respect to the IRNSS L5. The estimated code and phase standard deviations given in Table 2 (inset photo, above right) confirm this. We used the broadcast ephemeris for both constellations. Table 3 (inset photo, above right) provides further details on the data-set that we used.

Positioning and Ambiguity Resolution Analysis: Empirical and Formal
Here, we concentrate on the L5 positioning performance for both single-system IRNSS and dual-system IRNSS+GPS Block IIF. The data forming the basis of our analysis are one Hertz–sampled on DOY 183 of 2016. Table 4 (inset photo, above right) lists the single-epoch formal and empirical standard deviations of the CUBB-CUCC baseline components.

These results assume that the DD ambiguities are not yet fixed to their integer values, thus being called float solutions. Therefore, we obtained them by using the less precise code observations since the phase measurements are fully reserved for the DD ambiguities. Integrating IRNSS L5 with GPS L5 observations, the baseline estimation precision improves by three to four times horizontally and 2.5 times vertically.

Upon fixing the DD ambiguities, the very precise phase observations take the leading role in baseline estimation. The improvement of the ambiguity-resolved estimations, known as fixed solutions, with respect to their float counterparts, is a factor of 130 in case of standalone IRNSS and 150 in case of IRNSS+GPS Block IIF.

Figure 3 depicts the single-epoch one-second horizontal scatter plot (a) and height time series (b) of the CUBB-CUCC baseline float solutions (in gray), correctly fixed solutions (in green) and wrongly fixed solutions (in red) on the basis of L5 observables of IRNSS+GPS Block IIF collected on DOY 183 of 2016 with the cut-off angle of 10 degrees. The non-ellipsoidal shape of the scatter plot is due to the significant changes that the receiver-satellite geometry experiences during the 24-hour period. The panel (b) also contains the 95 percent formal confidence interval based on the float height standard deviation of which the signature is in good agreement with that of the height error time series, confirming the consistency between data and model.

The occurrence of incorrect ambiguity fixing can be explained by the easy-to-compute scalar diagnostic ADOP (ambiguity dilution of precision) introduced in the article by P. J. G. Teunissen (1997) and referenced in the Additional Resources section near the end of this article. It is defined as the square root of the determinant of the ambiguity variance matrix raised to the power of one over the ambiguity dimension. As a rule of thumb, an ADOP smaller than about 0.12 cycle corresponds to an ambiguity success rate larger than 99.9 percent, as introduced in the article by D. Odijk and P.J. G. Teunissen, (2008) (see Additional Resources). The panel (c) of Figure 3 depicts the time series of the single-epoch ADOP corresponding with IRNSS+GPS Block IIF L5.

Comparing the time series of the ambiguity-fixed height solution with that of the ADOP, the incorrect ambiguity fixing happens during the periods when ADOPs are larger than the value of 0.12 cycle. During some periods such as UTC [03:00- 05:00], although the float height solution shows large fluctuations, the DD ambiguities can still be correctly fixed. Therefore, while a receiver-satellite geometry can be poor for positioning, it can still be strong enough for ambiguity resolution.

As our measure to assess the integer ambiguity resolution performance, we made use of the ambiguity resolution success rate, known as the probability of correct integer estimation described in the article by P. J. G. Teunissen (1998). The 24-hour average single-epoch formal and empirical success rates were in good agreement with each other, confirming the consistency between model and data. The results also showed that upon integrating IRNSS with GPS Block IIF, the single-epoch integer ambiguity resolution success rate improves dramatically from about Ps =15% to Ps = 94%.

Ambiguity Resolution Performance for a Kinematic IRNSS User
The demonstrated consistency between our formal results and their empirical counterparts indicates that the easy-to-compute formal values can indeed predict the expected ambiguity-resolution performance. Here, we turn our focus from a single-epoch scenario to a multi-epoch scenario and conduct a formal analysis of the required number of epochs to fix the DD ambiguities with the success rate of Ps =99.9%. In that regard, we consider several onshore locations over the IRNSS primary and secondary service area (see Figure 4).

Remaining constant over time (in case of no loss-of-lock or cycle slip), the ambiguity resolution performance can improve if this time-constancy is exploited through a kalman filter. For both geodetic survey-grade receivers and low-cost receivers, we compute a 24-hour time series of the number of epochs needed to fix the DD ambiguities with Ps = 99.9% for a kinematic user in the framework of different underlying models. In order to show the statistical properties of these time series schematically, we make use of the boxplot concept introduced in the article by John W. Tukey (1997) referenced in the Additional Resources section near the end of this article. Our boxplot results are based on a 30-second sampling rate.

Geodetic Survey-Grade Receiver Results. Results presented in this subsection are on the basis of four underlying models, i.e., standalone IRNSS, IRNSS+GPS Block IIF, (fully-operational) standalone GPS III, and IRNSS+GPS III. We did not consider the case of standalone GPS Block IIF as this constellation contains only 12 satellites, thus having sometimes fewer than four satellites visible at different locations within the IRNSS service area.

For the geodetic survey-grade receiver, the zenith-referenced code standard deviation that we use for the GPS L5-signal is σ_pG = 20 cm — as introduced in an article by Nandakumaran Nadarajah et alia (2015) (Additional Resources) — and for IRNSS L5-signal is σ_pI = 30 cm, which is considered less precise than the GPS L5-signal (see Figure 2). The phase standard deviation for both systems is taken as σ_φG = σ_φI = 2mm.

Figure 5 shows the boxplots of the number of epochs to fix the ambiguities with Ps = 99.9%. Each panel contains, from left to right, the results of kinematic standalone IRNSS, IRNSS+GPS Block IIF and standalone GPS III, which are abbreviated in the legend to I, I+GIIF and GIII, respectively. Note that the results of the IRNSS+GPS III are not illustrated as this scenario always provides users within the IRNSS service area with the instantaneous ambiguity resolution with Ps = 99.9%, hence, the single-epoch RTK positioning. Also we did not show the standalone IRNSS results when the 75th percentile is larger than 50 epochs.

In order for our boxplots to be more readable, we used two vertical axes with different ranges in each panel. The boxplots to the left of the shown gray line should be read according to the left axis, and those to the right of the gray line should be read according to the right axis. From Figure 5, the following conclusions can be made:

• Regarding the standalone IRNSS, as one goes further away from the central location (φ=0°; λ=83°), the ambiguity resolution performance gets poorer. Excluding the locations within (0°< φ <20°; 65°< λ <101°), the standalone IRNSS user needs a considerably long time to fix the DD ambiguities with Ps = 99.9%.
• Integration of the IRNSS with the GPS Block IIF brings a huge benefit to the users within the IRNSS service area, especially for those on the border of the secondary service area. Nearly instantaneous ambiguity resolution and RTK positioning is feasible during the whole day for those locations within (0°< φ <20°; 65°< λ <101°). 
• As to the standalone GPS III performance, one can see that on average fewer than 10 epochs are needed to fix the DD ambiguities with Ps = 99.9%. 
• Given Ps = 99.9%, IRNSS+GPS III always provides the users within the IRNSS service area with the instantaneous ambiguity resolution and, hence, single-epoch RTK positioning.

Low-Cost Receiver Results. Thus far, with Ps =99.9%, we have shown that the ambiguity resolution can be carried out almost instantaneously when using GPS III L5, and instantaneously when using IRNSS+GPS III L5. Now, we will assess the ambiguity resolution performance of these two underlying models when using low-cost single-frequency receivers. For such receivers, the zenith-referenced observation standard deviations are taken as σ_pI = 100 cm, σ_pG = 75 cm and σ_φG = σ_φI = 3 mm.

Figure 6 shows the boxplots of the number of epochs needed to fix the ambiguities with Ps = 99.9%, for GPS III L5 (Left) and IRNSS+GPS III L5 (Right), which are abbreviated in the legend to GIII and I+GIII, respectively. From this figure, one can conclude:

• For the single-system GPS III, on average fewer than 20 epochs are required to fix the DD ambiguities.
• Integrating GPS III with IRNSS, almost instantaneous (less than five epochs) ambiguity resolution becomes feasible at all the locations within the IRNSS service area. Therefore, almost instantaneous RTK positioning would become possible.

Summary and Conclusion
For the fully operational IRNSS as a standalone system and also in combination with GPS, we have provided a first assessment of L5 integer ambiguity resolution and positioning performance. Following an empirical analysis and showing the consistency between data and model, we performed a formal analysis of the number of epochs needed to successfully fix the DD ambiguities for a kinematic user within the IRNSS service area for both geodetic survey–grade and low-cost single-frequency receivers.

Given a geodetic survey-grade receiver, the standalone IRNSS user needs quite a long time to fix the DD ambiguities. Meanwhile, the IRNSS+GPS Block IIF as well as the standalone GPS III user can carry out almost instantaneous RTK positioning during the whole day for most of the locations within the IRNSS primary service area. With such a high-grade receiver, single-epoch RTK becomes feasible provided that IRNSS is integrated with GPS III. Switching from geodetic survey-grade to low-cost receivers, this integration can still provide almost instantaneous RTK positioning at all the locations within the IRNSS service area.

Additional Resources
[1] Bensky, A., Wireless Positioning Technologies and Applications, Artech House, 2016
[2] GPS Directorate, Navstar GPS Space Segment/ User Segment L5 Interface Specification (IS-GPS- 705B), 2011
[3] GPS World, “First GPS III Satellite Completes Critical Test,” available online here, published January 19, 2016, accessed August 9, 2016
[4] Indian Space Research Organization, Indian Regional Navigation Satellite System: Signal in Space ICD for Standard Positioning Service, Version 1.0, ISRO Satellite Centre, June 2014
[5] Indian Space Research Organization, PSLV-C33/IRNSS-1G, available here, published April 2016; accessed June 1, 2016
[6] Lockheed Martin, “Lockheed Martin Powers on the First GPS III Satellite,” available here, published February 28, 2013; accessed 9 August 2016
[7] Marquis W., and M. Shaw (2016), "GPS III: Bringing New Capabilities to the Global Community,” September/October 2011, Inside GNSS, pp. 34–48, accessed August 9, 2016.
[8] Nadarajah N., and A. Khodabandeh, P. J. G. Teunissen PJG, “Assessing the IRNSS L5-Signal in Combination with GPS, Galileo, and QZSS L5/E5asignals for Positioning and Navigation,” GPS Solutions 20(2):289–297, 2015
[9] Odijk, D., and P. J. G. Teunissen, “ADOP in Closed Form for a Hierarchy of Multi-Frequency Single-Baseline GNSS Models,” Journal of Geodesy 82(8):473–492, 2008
[10] Teunissen, P. J. G., (1997), “A Canonical Theory for Short GPS Baselines. Part I: The Baseline Precision. Journal of Geodesy 71(6):320–336
[11] Teunissen, P. J. G., (1998), “Success Probability of Integer GPS Ambiguity Rounding and Bootstrapping,” Journal of Geodesy 72(10):606–612
[12] Tukey, J. W., Explanatory Data Analysis, vol 1, Reading, Mass: Addison-Wesley Publishing Co., 1977

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Incorporation of real-time synchronized phasor measurements in the control of power grids can play an important role in maintaining the overall closed-loop stability of the power system. In the past, instability in the power grid caused disturbances ranging from small local perturbations to severe large scale blackouts as can be seen from Figure 1. Currently, the synchronization achieved in measurements collected using devices known as supervisory control and data acquisition (SCADA) is not robust enough for efficient monitoring the power grid.

Incorporation of real-time synchronized phasor measurements in the control of power grids can play an important role in maintaining the overall closed-loop stability of the power system. In the past, instability in the power grid caused disturbances ranging from small local perturbations to severe large scale blackouts as can be seen from Figure 1. Currently, the synchronization achieved in measurements collected using devices known as supervisory control and data acquisition (SCADA) is not robust enough for efficient monitoring the power grid.

Modern power systems can benefit from deploying phasor measurement units (PMUs) as they provide synchronized measurements of up to 60 observations per second in regard to the current state of the system. The operation of PMUs greatly relies on precise time-keeping sources, such as GPS signals, to obtain absolute time for synchronization.

However, traditional GPS signals are of low power and unencrypted thereby making them susceptible to external timing attacks. In this article, we propose a novel multi-receiver direct time estimation (MRDTE) algorithm which utilizes the concept of maximum likelihood estimation.

This current setup is an extension of our earlier work focusing on single receiver direct time estimation (DTE), described in the paper by Y. Ng and G. X. Gao (2016) listed in Additional Resources near the end of this article. This prior article illustrated and verified the ability of DTE to detect meaconing attacks at an early stage and tolerate high noise levels. This multi-receiver architecture uses the information from spatially dispersed receiver locations to improve noise resilience and reduce the influence of external timing attacks.

Multi-Receiver Direct Time Estimation
With an aim to improve the robustness of our time-estimation method, we developed an extension that we named as multi-receiver direct time estimation. We propose the placement of multiple static antennas with pre-evaluated 3D position and velocity at different corners in the same power sub-station. Utilizing the geographical diversity in the receiver locations, the signals from different receivers are collectively analyzed to mitigate the effect of localized spurious signals.

In our setup, there are L different receivers that receive GPS signals from N visible satellites at any time instant t. All the receivers are triggered by the same common external clock. Different cable lengths introduce a bias across the receivers that can be pre-accounted for. Thereby, the clock states are considered to be the same across the receivers, as indicated in equation (1).

X_t,k : 3D Position and velocity of the k^th receiver at t^th time instant = [x_k, y_k, z_k, ẋ_k, ẏ_k, ż_k]_t
T_t,k : Clock states of the k^th receiver at t^th time instant = [cδt_j, cδṫ_j]          (1)   

The higher level architecture of the MRDTE described in Figure 2 consists of two major steps. The first step involves applying a novel signal processing technique known as DTE.

In the second step, known as MRDTE filter, the DTE outputs obtained from the receivers are collectively processed through an overall kalman filter. The corrected overall clock vector T_t,overall at any time instant t obtained as the output from MRDTE, is given as input to the PMUs. This strategy is adopted to reduce the search space from 8L (X_t,k, T_t,k) to 2 (T_t,overall), thereby increasing the robustness and decreasing the computational complexity.

Direct Time Estimation
DTE estimates the cumulative satellite vector correlation of the raw received GPS signal with the signal replica produced from each grid point g_j = [cδt_j, cδṫ_j] in a pre-generated 2D-search space (total M grid points). Taking the 3D position and velocity of the static receiver as the a priori information, the most plausible clock state of the receiver is evaluated based on the principle of maximum likelihood estimation, as shown in equations (2) through (4) (see inset photo, above right, for equations).

Equation (2)
Equation (3)
Equation (4)

The corresponding satellite channel delay residual is directly proportional to the clock bias residual, and the channel doppler residual is proportional to the clock drift residual. Given this, the channel delay and carrier doppler estimation are split into two parallel threads and independently estimated. (See Figure 3.)

Correlations are performed on a per satellite channel basis to obtain the correlation amplitude with respect to the code residual in Figure 4a while fourier transforms are carried out in parallel to obtain the spectrum magnitude with respect to the carrier doppler residual as shown in Figure 4b.

Non-coherent summation of the correlation amplitudes and spectrum magnitudes is computed respectively across the N visible satellites. These obtained summation of correlation values are allocated as weights that represent the likelihood of a particular g_j in the 2D-search space.

MRDTE Filter. After obtaining, the measurement error vectors e_k for each of the individual receivers, an individual receiver level measurement update T_t,k is done using a kalman filter. The next stage involves incorporating the individual receiver corrected clock parameters T_t,kk into an overall kalman filter to obtain the final corrected clock state T_t,overall corresponding to the common shared clock.

The overall measurement update at any instant t is: 

Equation (5)

The prediction of the overall and individual receiver states for the next time instant t+1 is achieved by linearly propagating the clock parameters based on the first order state transition matrix.

Initialization of MRDTE. The initialization T_0,k for each receiver can be done using any commercial techniques like scalar tracking etc. or by considering an optimum initial search space. Given that power grid is a static system, the receiver locations can be accurately pre-determined using the already available off-the-shelf techniques and averaged over time to get the best 3D position and velocity estimate.

Experimental Setup
To evaluate our MRDTE approach, we set up a field experiment, as described in the following section.

Hardware setup. We validated the robustness of the proposed multi-receiver DTE using four GNSS antennas mounted onto the roof of Talbot Laboratory, University of Illinois at Urbana-Champaign, as shown in Figure 5.

The antennas are connected to a common chip scale atomic clock (CSAC), chosen for its low drift rate, to form a receiver network, and the raw voltage data are logged using respective universal software radio peripherals (USRPs) each equipped with a daughterboard as in Figure 6.

Software Setup. GNUradio, a free opensource software development toolkit that provides signal processing blocks to implement software radios, was used for collecting the raw GPS L1 signal samples from USRP at a sampling rate of two megahertz. We chose to implement this technique in the python software-defined radio developed in our lab (pyGNSS), given its flexible and object-oriented framework. In our case, the 3D position and velocity of the receivers are calculated using multi-receiver vector tracking as described in the article by Y. Ng and G. X. Gao (2015) listed in Additional Resources. For the vector correlation, we opted for a coherent integration time of ΔT = 20ms. The measurement noise covariance matrix is evaluated using the covariance of the last 20 individual measurement residuals.

Results and Analysis
Virtual timing attacks, which include jamming and meaconing, are simulated and added onto the field data collected after which they are processed using MRDTE as discussed previously. While subjected to these external attack scenarios, we test the performance of MRDTE to that of conventional scalar tracking. Jamming. Jamming involves broadcasting a high-power noise signal near the GPS frequency range thereby causing the GPS receivers to lose track of the signal being acquired. The conditions of jamming are generated by adding white Gaussian noise A_ej2πΦt onto the incoming received signal. This noisy signal includes two components: random amplitude A, which is a measure of the strength of the noise being introduced and random phase Φ.

Figure 7 is indicative of the robustness of the MRDTE algorithm. In the presence of 12 decibels added noise, the scalar tracking loses track. However, the MRDTE still successfully tracks the signal accurately.

In Figure 8, the clock bias and clock drift residuals are compared for added noise with respect to the signal noise floor. In the presence of 5 decibels of added noise, the clock bias is estimated with an error of within 10 nanoseconds and, in the case of 12 decibels of added noise, within an error of 100 nanoseconds. Thus, a more robust clock state is estimated by implementing MRDTE algorithm.

Meaconing. In this case, a replay signal with similar GPS signal structure and signal power two decibels more than that of the authentic signal is added onto the incoming GPS signal. The first 36 seconds correspond to that of scalar tracking and after which the spurious signal is introduced represented by the thick black dotted line. At this point we turn on the MRDTE algorithm and compare its performance to that of scalar tracking for the next 30 secs.

When meaconing starts, the scalar tracking locks onto the counterfeit signal as shown in Figure 9 whereas the MRDTE still consistently tracks the authentic signal thereby mitigating the effect of meaconing attack.

Conclusions
This article proposed a novel MRDTE algorithm for secure and robust GPS time transfer using multiple static receivers sharing a common external clock. We leveraged the information redundancy and the known 3D positions of receivers to improve the robustness of the system. We implemented MRDTE using commercial available front-ends and our software platform PyGNSS. Through simulations of timing attacks based on GPS signals collected in field experiments, we demonstrate MRDTE’s increased resilience against jamming and meaconing attacks.

Acknowledgment
This material is based upon work supported by the Department of Energy under Award Number DE-OE0000780. This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.

Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

Additional Resources
[1] Adamiak, M., and R. Hunt, Application of Phasor Measurement Units for Disturbance Recording, Protection and Control Journal, Spring 2009
[2] Chou, D., and Y. Ng, and G. Xingxin Gao, Robust GPS-Based Timing for PMUs Based on Multi-Receiver Position-Information-Aided Vector Tracking, ION International Technical Meeting 2015, Dana Point, California, January 2015
[3] Closas, P., and C. Fernandez-Prades, and J. Fernández-Rubio et al., “Maximum likelihood estimation of position in GNSS,” Signal Processing Letters, IEEE, vol. 14, no. 5, pp. 359–362, 2007.
[4] Hart, D.G., and D. Uy, V. Gharpure, D. Novosel, D. Karlsson, and M. Kaba, “PMUs A New Approach to Power Network Monitoring,” ABB Review, 2001
[5] Misra, P., and P. Enge, Global Positioning System: Signals, Measurements and Performance Second Edition. Lincoln, MA: Ganga-Jamuna Press, 2006
[6] Ng, Y., and G. X. Gao (2016), Robust GPS-Based Direct Time Estimation for PMUs in Proceedings of the IEEE/ION PLANS conference, Savannah, 2016.
[7] Ng, Y., and G. X. Gao (2015), Advanced Multi- Receiver Vector Tracking for Positioning a Land Vehicle in Proceedings of the Institute of Navigation GNSS+
[8] Schweitzer Engineering Laboratories, “Improve Data Analysis by TimeStamping Your Data,” The Synchrophasor Report, May 2009, vol. 1, no. 3. conference (ION GNSS+ 2015), Tampa, 2015

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China’s development and promotion of its BeiDou satellite navigation system not only has tremendous implications for that country’s government and finances, but this alternative to GPS also presents a variety of implications for the United States, according to a staff research report released by the U.S.-China Economic and Security Review Commission.

The report, “China’s Alternative to GPS and its Implications for the United States,” was written by Jordan Wilson, policy analyst in security and foreign affairs at the U.S.-China Economic and Security Review Commission, and released on January 5, 2017. Congress established the commission in 2000 “to monitor, investigate, and submit to Congress an annual report on the national security implications of the bilateral trade and economic relationship between the United States and the People’s Republic of China, and to provide recommendations, where appropriate, to Congress for legislative and administrative action.” The Commission is composed of 12 members who serve two-year terms, three of whom are selected by each of the majority and minority leaders of the Senate, and the speaker and the minority leader of the House of Representatives.

Although BeiDou is provided for free and therefore is not designed to “compete” with other satellite navigation systems, including GPS, the commission noted that Beijing has implemented a number of domestic policies to promote the adoption of BeiDou-compatible receivers and expand its GNSS industry.

Plenty of reasons exist to believe this expansion will be substantial, Wilson writes. Not only are expectations high for significant economic growth brought on by BeiDou, but the development of one of the world’s first satellite navigation systems will also affect diplomatic issues and should also play a big role in providing China with both domestic and international prestige.

The Commission’s report states that, according to Davof Xu, GNSS China project manager for the European Union Chamber of Commerce in China, more than 14,000 companies and organizations are active in the GNSS-related industry in China, accounting for a total of more than 450,000 employees. Xu’s comments came from a commission staff interview last September.

The industry’s fast-paced growth along with China’s “relatively low current market share, latecomer status, and fragmented market likely indicates to Beijing an opportunity for significant economic benefits down the road,” the report states. An earlier report prepared for the U.S.-China Economic and Security Review Commission, “Planning for Innovation: Understanding China’s Plans for Technological, Energy, Industrial, and Defense Development,” by the University of California Institute on Global Conflict and Cooperation (IGCC) on July 28, 2016, said that Chinese GNSS companies are mostly small- and medium-sized in comparison to highly consolidated global providers.

In the commission’s January 5 report, commercial implications for both the U.S. and China are addressed. Wilson writes that the global trend toward “product compatibility with multiple constellations may actually create additional opportunities for U.S. companies in China in the near term.” He cites both the IGCC report and Qualcomm Inc.’s press releases to support these findings. Qualcomm that provided the GNSS component technology for the first GPS- and BeiDou-compatible smartphone — the China market version of the Samsung Galaxy Note 3 — in 2013.

China’s public release of BeiDou’s Open Service interface control document (ICD) as other GNSSs have done indicates a desire for some level of international participation. (The most recent version, BeiDou ICD v2.1, was released last November.) An official with the China Satellite Navigation Office noted in 2014 that “Chinese companies can only grow by engaging in face-to-face competition with the world’s top companies in the industry.”

The report notes, however, that it takes roughly one to two years to add a new constellation to product software, which can be a disadvantage for foreign companies that have not yet developed BeiDou compatibility. Additionally, Wilson said that China’s government has taken steps to advantage domestic companies, which most other GNSS programs have done at some point in their development. These steps include:
• Chinese companies were given early access to BeiDou reference designs and specifications, providing an early advantage in developing BeiDou products.
• China has established certification hurdles seemingly targeting non-Chinese vendors.
• According to the report, Qualcomm was not allowed to join China’s GNSS standards committee alongside domestic firms.

Because of these factors, U.S. and other foreign firms will likely need some time to take advantage of the commercial shift toward multi-constellation devices to compete in China’s domestic market.

In the international market, U.S. companies will likely be able to configure their products to work with the constellations prevalent in each region and compete with fewer obstacles than in China’s domestic market, the report argued. From this perspective, rapid movement towards full interoperability between satellite navigation systems will continue to be in the interests of the United States, the report indicates.

Challenges specific to the downstream satellite navigation industry in China should be included in larger discussions regarding U.S.-China trade and market access issues. As Mr. Xu observes, market access for foreign firms in China is a “general not a particular problem.”

More on BeiDou
China’s Beidou satellite navigation system is projected to achieve global coverage by 2020, providing position accuracies better than 10 meters (one meter or less with regional augmentation) using a network of 35 satellites. China has sought to field its own satellite navigation system for a variety of reasons.

According to the executive summary in Wilson’s report, China’s reasons include to: (1) address national security requirements by ending military reliance on GPS; (2) build a commercial downstream satellite navigation industry to take advantage of the quickly expanding market; and (3) achieve domestic and international prestige by fielding one of only four such global navigation satellite systems (GNSS) yet developed, cementing China’s status as a leading space power and opening the door to international cooperation opportunities. BeiDou is consistently referenced as one of China’s top space projects in its government white papers on space activities, most recently in December 2016.

Without a doubt, Wilson asserted, BeiDou is of foremost importance in allowing China’s military to employ Beidou-guided conventional strike weapons if access to GPS were denied. In addition to the open service, BeiDou transmits an encrypted signal intended for military or security use, as most other GNSSs also do.

In terms of specific security issues, the report notes that “concerns have been raised regarding inherent security vulnerabilities in BeiDou-equipped receivers.” These included the possibility of tracking users without their knowledge or introducing “malware” into their products, suggestions that Wilson indicated were raised by the Ministry of Science and Technology of Taiwan, with which mainland China has a problematical relationship. Technical experts interviewed for the report, however, noted that (1) they are not aware of ways to feasibly transmit malware through a navigation signal; and (2) receiver chip manufacturers outside China will be unlikely to include the BeiDou “texting service” due to cost factors.

Jim Mollenkopf, senior director of strategic development for Qualcomm Government Technologies, stated that “Qualcomm’s products only use BeiDou for passive reception of navigation signals, and do not use the BeiDou messaging function. We know of no way for the BeiDou system to track users without the messaging function enabled.”

Lastly, Wilson states that given that one-third of the smartphones exported from China in the first quarter of 2016 reportedly contained BeiDou receiver chips, U.S. consumers should know that there are no inherent risks involved in a smartphone having BeiDou connectivity if it does not include the satellite communication channel. The report cites Stephen Chen, “China to Massively Increase Accuracy of its GPS Rival, with Benefits for Smartphone Users … and the Military,” from the South China Morning Post (June 17, 2016) with providing these figures.

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After a yearslong wait the Federal Communications Commission (FCC) is asking for comments on whether it should allow signals from Europe’s Galileo satellite navigation system to be used for non-federal applications in the United States. The call for public feedback is part of a process to grant a waiver so that Galileo-capable receivers don’t have to be licensed in the United States.

The licensing mandate, which has its roots in the World Trade Organization (WTO) Telecom Agreement of the late 1990s, only came to public attention roughly two years ago. This is despite the fact that the Galileo constellation has been broadcasting since 2011 and its signals already have been integrated into most, if not all, commercial GNSS receivers. The waiver, however, would make it possible to incorporate Galileo into government official uses like Enhanced 911.

In 2015 the FCC determined that a plan proposed by the major wireless carriers to tap Galileo to improve the locatability of distressed cellphone callers could not be used to meet the FCC’s emerging E911 requirements because the Galileo system was unauthorized — that is the licensing/waiver requirement had to be met. Given the upward trends in cellphone adoption and the difficulty of locating callers horizontally, that is in apartment buildings, the decision was arguably significant for public safety.

Comments Please
In the FCC’s request, which can be found in docket 17-16, the agency asks for feedback on whether it should "permit non-Federal receive-only earth stations within the United States" — that is GNSS receivers — to use the Galileo E1, E5 and E6 signals. These signals are transmitted on the bands 1559-1591 MHz (E1); 1164-1219 MHz (E5); and 1260-1300 MHz (E6).

The National Telecommunications and Information Administration (NTIA), which manages government’s use of frequencies, submitted the request to the FCC in January 2015. NTIA assessed the request from the federal users’ perspective after the European Commission submitted it to the State Department in 2012. In its letter, NTIA noted that U.S. policy embraces the prospect of foreign constellations being used to augment and strengthen the resiliency of GPS signals.

In its request for comments the FCC noted the extensive coordination of the U.S. and European systems and that both sets of satellites use the same band of internationally coordinated frequencies. The agency stressed that it agrees with the NTIA, which did not find any interference issues. The FCC wants confirmation that that is the case, however, and to give the public an opportunity to comment.

Ligado
Telecom regulators are asking for information ranging from possible issues with Galileo’s signal structure to details about satnav receivers. The request for receiver information may reflect the issue that has most likely been holding up the waiver — how approving Galileo would impact the use of bands near the satellite navigation frequencies.

The FCC has been searching for ways to allocate more spectrum for wireless broadband and has been weighing a proposal from the firm Ligado to recast frequencies near those used by GPS and Galileo to support a plan for a terrestrially-focused broadband network. That company, initially named LightSquared, incorporates ancillary terrestrial components or ATCs — ground stations that potentially would put out signals of much higher power than the mobile satellite signals for which the band was originally allocated. After then-LightSquared filed for approval in 2010, tests showed that its signals would overpower the vast majority of GPS receivers. The plan has since been modified but significant concerns remain.

The FCC wants to know how GPS and dual constellation receivers "are currently designed to receive the Galileo signals and/or GPS signals and the receivers’ electromagnetic compatibility with other uses of spectrum in the RNSS bands or adjacent or nearby bands." Among other things it’s asking if designing receivers for constellations other than GPS and Galileo might make those devices "more susceptible to receiving potential interference from non-Federal transmitters that operate below 1559 MHz and/or above 1610 MHz which could affect the electromagnetic compatibility of these GNSS and non-Federal operations."

Ligado, which is mentioned in the request for comments, has asserted in at least one previous filing that organizations seeking to license their receivers must agree to accommodate their neighbors. The issue brings up questions about protection of the Galileo, which uses frequencies in the band for satellite navigation but closer to the frequencies Ligado wants to use.

Comments must be submitted to International Bureau (IB) Docket 16-17 by February 21 with reply comments due March 23.

DoD Weighs In
The NTIA has the authority to grant waivers/authorizations for federal users, so the Department of Defense and other national government users have not been kept in limbo. In fact, the DoD recently told lawmakers it is quite interested in the Galileo signal.

Less than a week after the FCC published its request the DoD sent Congress a report lawmakers had requested as part of the 2017 National Defense Authorization Act (NDAA). Galileo will offer "a worldwide, accurate, and timely" positioning, navigation, and timing (PNT) service when it is fully operational in roughly three years, the agency wrote. Its signals are compatible with GPS, "simplifying the technical changes needed for receivers to benefit from the use of both GPS and Galileo," and Galileo’s Public Regulated Service (PRS) signal would provide a second, space-based source of secure PNT information for critical United States civil, private sector and potentially national security users.

"GPS has become inextricably interwoven into the conduct of global commerce and military operations; however, as multiple DoD and civil PNT studies have concluded, GPS’s very utility and importance underscores the need to ensure that there is resilience for GPS," the Pentagon told lawmakers. "…DoD users can obtain additional resiliency and accuracy by using signals from both Galileo and GPS satellites." The benefits of such resiliency extend to the private sector, which holds most of the nation’s critical infrastructure and relies heavily on PNT, the authors pointed out.

According to the report, the additional satellites would help users in limited-sky situations. Moreover adversaries would find it more difficult to deny both GPS and Galileo, "particularly given that Galileo is a multinational capability."

DoD also would benefit from the creation of a U.S. commercial multi-GNSS industrial base that DoD could draw upon. Military officials pointed out that if they wanted to buy American manufactured, dual-capable GPS and Galileo commercial receivers, it was "highly likely" they only would be available if the FCC approved the European request for a waiver. Moreover, they said, the U.S. receiver industry would have more opportunities to build and sell dual-capable GPS and Galileo receivers around the world, thereby allowing them to compete more effectively with EU commercial providers.

Finally, approval of Galileo use in the United States "would help advance the U.S. Government-EC negotiations for U.S. access to the Galileo PRS encrypted signal for civil and national security-related activities," said the DoD.

"In my view," said Scott Pace, the director of the Space Policy Institute at the Elliott School of International Affairs at George Washington University, "the DoD report to Congress reiterates the position of the Administration when it sent the waiver request to the FCC in the first place. It is in the public interest to grant the waiver and allow Galileo signals to be received and used in the United States. That said, considering language in the NDAA — raising questions about use of foreign systems like GLONASS — it’s not unreasonable for Congress to ask for the DoD’s viewpoint. DOD’s support for granting the waiver recognizes the resiliency value of having access to multiple GNSS sources, particularly one provided by NATO allies, and the waiver helps strengthen the U.S. industrial bases on which DoD relies."

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