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

1. HAPPY BIRTHDAY!
Los Angeles, California USA
√ Congratulations to SVN 23, a GPS IIA satellite, for 20 glorious years. The GPS Directorate expects 12–18 months more of active duty from the overachieving space vehicle, which was expected to last only 7½ years. (Meanwhile, Europe’s first Galileo test satellite, GIOVE-A, was expected to last 27 months and is still cookin’ after five years.)

1. HAPPY BIRTHDAY!
Los Angeles, California USA
√ Congratulations to SVN 23, a GPS IIA satellite, for 20 glorious years. The GPS Directorate expects 12–18 months more of active duty from the overachieving space vehicle, which was expected to last only 7½ years. (Meanwhile, Europe’s first Galileo test satellite, GIOVE-A, was expected to last 27 months and is still cookin’ after five years.)

GPS Directorate, Los Angeles AFB: Global Positioing System Satellite Achieves 20 Years On-Orbit
European Space Agency: Galileo pathfinder GIOVE-A achieves five years in orbit

2. EMOTIONAL INTELLIGENCE
Cambridge, England
√ Watch out . . . your GPS unit soon may be empathic enough to change voice tones, decrease volume, and stop repeating instructions if you’re feeling grouchy. Cambridge University computer scientist Peter Robinson was so frustrated by his “difficult” GPS “built by sadists” that he and his researchers created a robotic prototype that identifies a driver’s feelings 70% of the time.

• See Professor Robinson and “Charles” in action
• University of Cambridge – “The Emotional Computer”
• Cambridge Computer Laboratory “Rainbow Research Group”: Emotionally Intelligent Interfaces

3. THE SATELLITES’ WAY
The Camino, Galicia, Spain
√ Last fall, a dozen pilgrims with disabilities covered 460 miles on the 1,000-year-old Way of St. James, a Christian pilgrimage from France to Galicia in northern Spain. They demonstrated tools that combine GPS, MP3, radio and audio, smart phones, and the web to show that satellite technologies make even the tough Camino accessible.

• The Satellites’ Way
• EGNOS “Modern Pilgrims Boost Satellite Navigation for All”

4. FIRST TIME
Dubai, United Arab Emirates
√ Time for the Middle East to get its own GNSS? In January, the UN International Committee on GNSS and the U.S. State Department organized the first regional workshop on GNSS in Dubai. “UAE officials could take the lead in incorporating existing systems in various applications and research, and creating [suitable] mapping .  . . or reference systems,” said ICG program officer Sharafat Gadimova in The National, a UAE newspaper.

• The National article

5. PAX PACIFICA
Tokyo, Japan
√ Government representatives from Japan and the United States met in Tokyo on January 13 for the eighth time since 1998 to reaffirm space-based PNT cooperation between the countries — free access, no direct user fees and interoperability among GPS, QZSS, MSAT, and WAAS — And to say that GNSS is indispensable to modern life and to Asia-Pacific development.

• “Joint Announcement on United States-Japan GPS Cooperation”
  U.S. Department of State website
  Ministry of Foreign Affairs of Japan website

The post GNSS Hotspots | January 2011 appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Russia’s GNSS program started off the year recovering from a series of setbacks that resulted in the dismissal of two space officials in the wake of the December 5 launch failure of three GLONASS-M satellites.

The postponed launch of the next-generation GLONASS-K demonstration spacecraft in 2010 meant that the program ended up the year with four fewer satellites in orbit than expected.

After technical and political setbacks, Russia gets ready to launch its first CDMA-equipped satellite in February.

Russia’s GNSS program started off the year recovering from a series of setbacks that resulted in the dismissal of two space officials in the wake of the December 5 launch failure of three GLONASS-M satellites.

The postponed launch of the next-generation GLONASS-K demonstration spacecraft in 2010 meant that the program ended up the year with four fewer satellites in orbit than expected.

Russia had anticipated declaring full operational capability (FOC) for GLONASS by March; now that may not occur until June, said Russia’s Federal Space Agency (Roscosmos) Director Anatoly Perminov said in a January 12 report by ITAR-TASS, Russia’s state news agency.

Constellation Status
The GLONASS-K launch, delayed due to incomplete preparations at the Plesetsk, Russia, launch site, now is expected to take place near the end of February. The prime contactor, ISS-Reshetnev, completed ground tests on the demonstration spacecraft in December.

The new model will broadcast the first GLONASS code division multiple access (CDMA) channelization protocol in addition to the system’s usual frequency division multiple access (FDMA) transmissions. That will bring the system into closer alignment with other GNSSes, which all use CDMA.

Perminov said the next launch of another three GLONASS-Ms is scheduled for August. As of January 18, the system showed 26 operational satellites in the GLONASS constellation with 21 of them transmitting healthy signals, according to the Roskosmos Information-Analytical Center, with the other five currently in “maintenance” status.

In response to the failure, two older, spare satellites in the constellation have been activated and moved to new orbital locations.

The system needs to have 24 actively transmitting satellites to support an FOC declaration. How many of those in maintenance status can be restored to service is uncertain, although all are fairly new — having been launched within the last five years. One of them (#726), however, has been off-line since August 31, 2009, due to a problem with the signal generator that appears unlikely to be fixed.

An additional consideration: GLONASS orbital plane 1 has only seven operational spacecraft, with one undergoing maintenance since last August. The nominal configuration of the constellation calls for eight satellites in each plane in order to provide the optimal geometrical coverage worldwide.

Consequences of Failure
In addition to dismissing the space officials in the wake of the December launch failure, Russian President Dmitry Medvedev reprimanded the head of Roscosmos.

A December 29 press statement from the Kremlin said, “Following the report presented to the President by Deputy Prime Minister Sergei Ivanov, a decision was made to remove from the office Vice-President and First Deputy General Designer of the S.P. Korolev Rocket and Space Corporation Energia Vyacheslav Filin and Deputy Head of the Federal Space Agency (Roscosmos) Viktor Remishevsky for the errors made in the calculations for refuelling the vehicle’s Block DM-3 upper stage. Head of the Russian Federal Space Agency Anatoly Perminov was reprimanded.”

The statement added, “In accordance with Dmitry Medvedev’s instructions, Roscosmos will take additional measures to reinforce disciplinary measures.”

RKK Energia manufactures spacecraft and space station components and is prime developer and contractor of the Russian manned spaceflight program.

The Proton-M rocket launched from the Baikonur facility in Kazakhstan on December 5 apparently had been equipped with larger fuel tanks that were then filled to capacity. The heavier load of liquid oxygen — reportedly 1.5 to 2 tons more than normal — apparently caused the launcher to deviate from its planned trajectory and fall into the Pacific Ocean more than 900 miles northwest of Hawaii, according to an inter-ministerial commission charged with investigating the launch failure.

The post GLONASS: Bumpy Road appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

The attitude is unfair, of course, as with so many stereotypes.

And also untrue.

For example, as the number of existing or planned GNSS systems grew during the past few years, the expression “Your signal is my noise” has recurred in the engineering community with increasing frequency.

I consider that an elegant, if ominous, turn of phrase. A simple declarative sentence, pithy, with an ironic edge, yet almost lyrical.

Most people probably don’t associate engineers and linguistic virtuosity.

The attitude is unfair, of course, as with so many stereotypes.

And also untrue.

For example, as the number of existing or planned GNSS systems grew during the past few years, the expression “Your signal is my noise” has recurred in the engineering community with increasing frequency.

I consider that an elegant, if ominous, turn of phrase. A simple declarative sentence, pithy, with an ironic edge, yet almost lyrical.

And in those five words rests a nut of truth that will be hard to crack.

They point to questions of GNSS compatibility and interoperability that are being raised ever more often in more places, including the International Communications Union (ITU), which arbitrates radio frequency allocations, and the International Committee on GNSS (ICG), a UN-sponsored organization that includes all the major players in the field today.

And they raise matters involving the laws of physics as well as the laws of nations.

Inexorably, each additional signal transmitted in the same band increases the thermal noise with which GNSS receivers must deal. Moreover, the use of spread spectrum techniques within limited bandwidths inevitably constrains the ability of system providers to maintain separation between signals.

In the absence of solid agreements on how to achieve compatible, interoperable services, the addition of signals becomes a bane, not a boon, to users of any and all GNSS systems.

To paraphrase Mark Twain, RF spectrum is a valuable commodity because they have quit making it. And like land, it only becomes more valuable as it becomes more crowded.

Recent technical studies raise the possibility that there may not be room for everybody comfortably, that three constellations, for example, might be the theoretical optimum for GNSS.

Spectrum may become the new gold rush. And frenetic races to secure the benefits of GNSS — political, economic, technological, and social — could cause much damage.

Making room for all GNSS systems, therefore, will require more, not less, cooperation and goodwill.

The efforts of groups such as the ICG, the ITU, and other standards-setting organizations active in the GNSS area represent a necessary condition for securing a harmonious synergy. But, as presently conceived, they are probably not sufficient to accomplish it.

In large part, this arises from their essentially voluntary nature. Even the ITU with its comprehensive global participation of national telecommunication agencies depends upon the willing compliance of its members to ensure compatible use of spectrum.

And independent bilateral talks can be even more problematical without the moral pressure of wider participation.

Over the past three years, for instance, the European Union and China have met five times in a technical working group on BeiDou/Galileo compatibility and interoperability, trying to resolve a conflict in the proposed overlay of a BeiDou-2 signal on Galileo’s Publicly Regulated Service (PRS). Thus far, without success.

Of course, examples of successful bilateral negotiations exist, but they are necessarily partial solutions to a complex problem.

Eventually, some entity will need to evolve that can bind members, however voluntarily they join it, to mutually agreed upon terms for ensuring compatible, interoperable GNSS services.

The post Your Signal Is My Noise appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

In the early stages of developing space-based radionavigation, the spectrum compactness of ranging signals was not proclaimed among the material priorities. Conventional bi-phase shift keying (BPSK) modulations, although they consume a rather large amount of spectrum, were adopted as the basis for both GPS and GLONASS signals.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

In the early stages of developing space-based radionavigation, the spectrum compactness of ranging signals was not proclaimed among the material priorities. Conventional bi-phase shift keying (BPSK) modulations, although they consume a rather large amount of spectrum, were adopted as the basis for both GPS and GLONASS signals.

Later developments, such as the modernized civil GPS L1-band (L1C) and military (M-code) signals as well as some signals of Galileo and Compass/BeiDou-2, modified the plain BPSK a bit to take a form of binary offset carrier (BOC) modulation, which again is in no way bandwidth-efficient.

In the meantime, scenarios arose in which the penetration of GNSS signals into neighboring bands allocated to other systems appears to be tangibly harmful. One example of this sort is the collision between L1 GLONASS signals and an International Telecommunication Union (ITU) requirement to keep quite a low level of any side power flux within the radio astronomy window at 1610.6–1613.8 MHz.

The trouble here is that the power amplifier of a standard satellite transmitter does not tolerate amplitude modulation; so, signal prefiltering is not an option. Currently the attempts are being undertaken to solve the problem by post-amplifier band rejection, compromising the transmitter energy output and mass-dimension characteristics.

Similar challenges may be expected all the more in the future with the anticipated advances of satellite radionavigation into new frequency bands, e.g. C-band. Attention to this possibility has recently been drawn in the articles by J.A. Avila-Rodriguez et alia and A. Schmitz-Peiffer et alia (see Additional Resources).

A radical way to organize navigation signals with a minimum out-of-band emission would be to replace traditional BPSK with some continuous-phase modulation (CPM), such as minimal shift keying (MSK) or one of its numerous enhanced analogs. Smooth changes in the complex amplitude of a CPM signal result in a very compact spectrum combined with the absence of amplitude modulation.

Owing to this characteristic, employing a CPM design in future GNSS signals could make it unnecessary to apply any post-amplifier rejection within the forbidden frequency range, or, at least, if a stop-band filter cannot be completely excluded, its implementation may turn out not that demanding. Similar ideas have already been put forward in the articles mentioned earlier and also in the article by V. Ipatov and B. Shebshaevich referenced in Additional Resources.

Of course, the bandwidth economy inherent to CPM is obtained at the cost of potentially compromising some other performance characteristics. Indeed, removal of high-frequency spectral components principally reduces root-mean-square signal bandwidth, thereby increasing the theoretically achievable noise error of the signal time-of-arrival estimate. Equally, one can expect degradation of multipath resistance again due to spectrum concentration within the narrower band.

In the sections to follow, however, we demonstrate that allowing for a limited bandwidth of the receiver frequency-selective circuits with preference to CPM modulation rather than BPSK often means either insignificant deterioration of these performance characteristics or even their improvement.

One more disputable issue is a way of aggregating two subsignals differing in bandwidth: narrowband (or civil) and wideband ones, into a united signal free of amplitude modulation. Creating this kind of combined signal does not present any difficulty if the modulation is BPSK or BOC, as takes place in GPS, Galileo, GLONASS, and other systems, where each of the subsignals modulates its own quadrature carrier component.

As amplitude modulation does not occur in quadrature components and they are phase-shifted by π/2 to each other, no amplitude modulation appears in the resulting signal either.

Replacement of BPSK with the CPM means that the ranging signal elements — chips — are not rectangular any more, and each of subsignals becomes amplitude-modulated. In the next section we describe how to construct subsignal chips in order to come to the amplitude-modulation-free overall signal incorporating both subsignals.

As long as various versions of spectrally efficient modulation exist and our goal is just to uncover their common potential merits stemming from the complex amplitude continuity, we can reasonably limit ourselves here to the simplest CPM mode, namely MSK.

Further complications of CPM, particularly making continuous phase derivatives along with the current phase itself, can lead to even greater spectrum compactness.

Possible Structure of an MSK-Based Satellite Signal
As is well known (see, for example, the textbooks by J. Proakis or B. Sklar cited in Additional Resources), the MSK is just a modified version of the offset quadrature phase shift keying (OQPSK). In conventional OQPSK, streams of rectangular elementary symbols (chips in our case) of two quadrature branches are time-shifted to each other by a half symbol length. To convert OQPSK to MSK we only need to replace a rectangular chip with one having the shape of sine half-wave of the same duration.

Due to a mutual time shift of quadrature streams, a change of chip polarity caused by ranging coding in one branch occurs when the other branch chip passes its maximum. As a result of the smoothness of a half-sine chip, the overall signal comprising both branches has no phase jumps. Moreover, the half-sine chip shape provides amplitude constancy of the overall signal.

To roughly assess the spectral saving of a modulation and its share of out-of-band emissions, one can resort to the 99 percent bandwidth, W_0.99, which is a frequency span containing 99 percent of the total emitted signal power. For BPSK with chip length Δ W_0.99 ≈ 20/Δ, which is 10 times larger compared to the traditional figure 2/Δ, estimating the bandwidth by the space between first spectral zeros. In contrast to this, for an MSK modulation with the same chip length W_0.99 ≈ 2.4/Δ, meaning more than an eightfold economy in the bandwidth actually occupied.

Let us base our further consideration on the premise that a future GNSS signal is to succeed the existing one in combining two (public and special) accuracy scales, meaning that it has to contain both narrowband (long-chip) and wideband (short-chip) components. At the same time, we can readily see from the previous discussion that, in order to implement an MSK discrete signal, the chips in both quadrature branches should be half-sines of the identical duration.

To reconcile these contradictions we propose to build both long-chip and short-chip components using universal short elements or microchips of duration δ (Figure 1a, above right). Then a civil (narrowband) component chip of duration Δ_n = n_nδ is a series of n_n microchips of the same polarity (Figure 1b), while a wideband component chip of duration Δ_w can be either a microchip itself (Δ_w = δ, Figure 1a) or a train of n_w pairs of sign-alternating microchips (Δ_w = 2n_w, Figure 1c).

The latter option corresponds to the implementation of the BOC-modulation mode through MSK, which can be used to partly separate civil and special components spectra.

To come to the resulting MSK signal the two components constructed in this way should just be used in quadrature, that is, modulating in phase (I) and in quadrature (Q) carrier waves. In so doing, one of them has to be in a preliminary fashion half-microchip–shifted against the second, as is shown in Figure 2 (above right) for the case n_n = 4, n_w = 1.

An important comment to the suggested construction of a narrowband component:  the simplest low-cost receiver has no need to reproduce the exact shape of chip of Figure 1b in a correlator reference. Instead, a conventional rectangular chip of length Δ_n could be used at the price of an energy loss of π²/8, that is, about 0.9 decibel.

In other words, if some day the GPS civil signal was switched to the proposed MSK modulation mode without changing ranging code, all existing commercial receivers would survive although suffering from the signal-to-noise (SNR) penalty as described.

. . .

Potential Accuracy of MSK Ranging
Our suggested signal gains spectral compactness compared to legacy modulations as a result of the smoothness of MSK chip. Theoretically, we pay for this compaction in the form of a degradation of the potential measurement accuracy of pseudoranges or, equivalently, the time of arrival (TOA), τ, of the satellite ranging code against the local time scale.

In practical calculations, however, we should allow for the finite bandwidth of both the transmitter and receiver and, if some realistic assumptions are made on this account, the accuracy of time measurement of the proposed signals appears to be no worse than with the existing ones.

. . .

Multipath Resistance
The issue of multipath resistance is among the most critical in designing GNSS signals and, again, at first glance it might seem that multipath performance of a smoothed chip is poorer than with a rectangular one. Nevertheless, in line with the previous section when the real receiver frequency selectivity is taken into consideration, an MSK-based signal appears completely competitive with the legacy ones.

In numerous sources, assessment of the multipath influence is demonstrated employing a graph of the code-tracking error envelope. Curves thus built depend critically on the discriminator type, strobe spacing, and strobe length, and for every possible chip shape these factors should be adjusted individually to optimize performance.

In this section we will follow an alternative approach that concentrates on the potential accuracy of measuring TOA of the line-of-sight signal distorted by multipath interference. By this means, we will find out to what extent the multipath is destructive in principle when applied to both traditional signals and our proposed modulation technique.

. . .

Conclusions
The following statements may briefly summarize our discussion:

• The MSK modulation and, in general, spectral-efficient modulation formats provide a productive tool for frequency coordination between the neighboring systems in the RF spectrum, particularly for mitigating the problem of penetration of GNSS emissions into the radio astronomy band.

• Within the MSK modulation mode the task of aggregating two sorts of signals: the narrowband (civil) and wideband ones can be feasibly solved by composing the narrowband chip as a series of short microchips.

• The potential accuracy of measuring TOA with the proposed MSK signals is either comparable or even better relative to the legacy signals as soon as realistic values of receiver bandwidth are taken into account.

• The same is true for the potential multipath resistance defined by the accuracy of the TOA estimate in the presence of multipath with a priori unknown delay and intensity.

• There is no need to reproduce an exact narrowband chip shape in a cheap commercial receiver: its replacement by a plain rectangle will lead to the energy loss within only 0.9 decibel.

• The analysis presented here is just a first step limited to the MSK format only. With an optimized microchip, we can expect to achieve even better performance.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

Additional Resources
[1] Avila-Rodriguez, J.-A., and S. Wallner, J.-H. Won, B. Eissfeller, A. Schmitz-Peiffer, J.-J. Floch, E. Colzy, and J.-L. Gerner, “Study on a Galileo Signal and Service Plan for C-Band,” Proceedings of GNSS 2008, Toulouse, France, April 22–25, 2008
[2] Groves, P., Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Artech House, 2008
[3] Hein, G., and J. Betz, A. Pratt, A.R., L. Lenahan, J. Owen, J., J.-L. Issler, and T. Stansell, “MBOC: The New Optimized Spreading Modulation Recommended for Galileo L1OS and GPS L1C,” Inside GNSS, Vol.1, No. 4, pp. 57-65, May/June 2006
[4] Ipatov, V., and B. Shebshaevich, “GLONASS CDMA: Some Proposals on Signal Formats for Future GNSS Air Interface," Inside GNSS, Vol. 5, No. 5, pp. 46-51, July/August 2010
[5] Proakis, J., Digital Communications, McGraw Hill, N.Y., 2001
[6] Schmitz-Peiffer, A., and A. Fernández, B. Eissfeller, B. Lankl, E. Colzy, J.-J. Floch, J.-H. Won, J.-A. Avila-Rodriguez, F. Stopfkuchen, M. Anghilery, O. Balbach, R. Jorgensen, S. Wallner, and T. Schüler, “Architecture for a Future C-band/L-band GNSS Mission. Part 2: Signal Considerations and Related User Terminal Aspects,” Inside GNSS, Vol. 4, No. 4, pp. 52–63, July/August 2009
[7] Sklar, B., Digital Communications, Prentice-Hall, Upper Saddle River, NJ, 2001
[8] Van Trees, H., Detection, Estimation and Modulation Theory, Part 1, John Wiley & Sons, 2001

The post Spectrum-Compact Signals appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

A European Commission (EC) communication sent to the European Parliament and European Council today (January 18, 2011) estimates that completing a fully operational capability (FOC), 30-satellite Galileo system and the European Geostationary Navigation Overlay Service (EGNOS) will cost an additional €1.9 billion above the €3.4 billion already allocated.

A European Commission (EC) communication sent to the European Parliament and European Council today (January 18, 2011) estimates that completing a fully operational capability (FOC), 30-satellite Galileo system and the European Geostationary Navigation Overlay Service (EGNOS) will cost an additional €1.9 billion above the €3.4 billion already allocated.

The EC report attributes the cost overruns primarily to the increased cost of the development phase, the increased price of the launchers, and the lack of competition for the award of some contracts in the deployment phase.

The commission says that about €500 million of those costs came as a result of the transition from a public-private partnership (PPP) model to an all-public program, including renegotiating contracts and the need to launch a second experimental satellite (GIOVE-A) in order to retain the use of RF frequencies allocated by the International Telecommunication Union (ITU). Another €500 million stems from the higher cost of launch services compared to the original contract.

Moreover, the EC foresees an average annual expense of €800 million to operate the systems.

Nonetheless, the communication states, “The ultimate objectives are not being called into question, because the budget available already encompasses the building and launch of 18 satellites, with the associated ground infrastructure, and the supply of the first services from 2014–2015.” The €3.4 billion also covers the initial operation of the EGNOS services.

In releasing the communication, European Commission Vice-President Antonio Tajani, Commissioner for Industry and Entrepreneurship said, "Galileo will allow Europe to compete in the global space technology market and to impose itself as one of the leading players in a growing sector characterized by increased internationalization and the entry of emerging economies. We are satisfied with the progress made so far and committed to bringing this project to fruition."

Assuming that the additional money is approved, the commission’s Galileo leaders now expect the FOC system to be completed in the 2019–2020 time frame. The EC is also proposing that EGNOS, essentially the European counterpart to the U.S. Federal Aviation Administration’s Wide Area Augmentation System (WAAS), be adapted so as also to improve the accuracy of the Galileo open service as well as GPS.

Pending reaction from parliament and the European Council, the commission will develop proposals for alternative methods of financing the project.

The post Galileo Mid-Term Review Foresees €1.9 Billion in Additional Costs appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Berry Smutny has become the first GNSS casualty in the WikiLeaks war.

The CEO of OHB-System AG was suspended  on Monday (January 17, 2011) "with immediate effect," according to the company.

Berry Smutny has become the first GNSS casualty in the WikiLeaks war.

The CEO of OHB-System AG was suspended  on Monday (January 17, 2011) "with immediate effect," according to the company.

OHB-System AG, the German company building the Galileo operational satellites, dismissed Smutny as the result of comments about the Galileo program that he reportedly made to U.S. embassy officials in Berlin, which appeared recently in documents released by WikiLeaks and published by Norway’s Aftenposten newspaper on January 13. When the news reports first appeared, the company had initially backed Smutny with a statement by Manfred Fuchs, chairman of the supervisory board.

In a January 17 press statement, however, the company said that OHB-System’s General Assembly had voted to remove its confidence in Smutny. Subsequently, the company’s "Supervisory Board passed a unanimous resolution to revoke Mr. Smutny’s appointment to the position of CEO of the company. This was in response to the fact that over the past few weeks the Norwegian daily “Aftenposten” had repeatedly published and commented on documents recording the contents of a conversation between Mr. Smutny and diplomats at the US embassy in Berlin. The Supervisory Board disapproves these conversations and the quotes attributed to Mr. Smutny."

The company’s statement added that the General Assembly and the Supervisory Board "saw no alternative to this decision in order to effectively avert any further damage to the company on the part of customers, political representatives and the public at large."

Marco R. Fuchs, the CEO of the parent company OHB Technology AG, will additionally be assuming the position of CEO of OHB-System AG until further notice and will share the duties of Smutny with the members of the management board, Dr. Fritz Merkle, who is responsible for the company’s business development, and Frank Negretti, board member in charge of security.

The Supervisory Board thanked Smutny for the work that he had performed over the past 18 months, particularly stressing the fact that last year had been the most successful in the company’s history.

The post OHB-System “Suspends” CEO over WikiLeaks Galileo Comments appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

A: A fairly good analogy of the difference between GNSS signal acquisition and tracking can be found in the rescue of victims of a sunken ship whose location is not accurately known. The first stage of the rescue attempt typically involves an aircraft flying a search pattern, which hopefully encompasses the location where the ship went down.

For two main reasons, spotters aboard the plane may have great difficulty finding a person afloat in a vast expanse of ocean. First, because the human eye is most sensitive in its relatively small area of central vision, the spotter must scan over a wide area to locate what appears to be a tiny spot on the ocean’s surface. Second, detecting a human figure can be very difficult among numerous whitecaps whipped up by the wind in a rough sea, which appears as “noise.”

The process of searching for a person at sea is analogous to the search required for acquisition of a GNSS signal.

However, once the victim is located (acquired), the spotters must keep the person in sight (tracked) for some period of time during rescue operations. The tracking process is generally much easier than acquisition, as the spotter now knows quite accurately where the person is located.

In this phase, the sophisticated tracking capability of the eye’s central vision area comes into play. Even momentary disappearance of the victim is not a problem, because reliable reacquisition is possible by performing a search over a very small area, and the clutter (noise) outside this area can be disregarded. This type of operation is analogous to tracking a GNSS signal.

For concreteness, we will compare the acquisition and tracking processes for a legacy L1 C/A-coded GPS signal from a single satellite, with simplifications that facilitate understanding. In this case acquisition sensitivity is defined as the minimum signal power required for a specified reliability of correct acquisition, with a similar definition for tracking sensitivity.

Although with enough processing there is no theoretical limit for either, the sensitivity for tracking in GPS receivers is generally better (typically about two to five decibels lower in signal power) than for acquisition.

Why does this happen?

When a typical GPS receiver is turned on, the following sequence of operations must occur before the receiver can access the information in a GPS signal and use it to provide a navigation solution:

1.     Determine which satellites are visible to the antenna.
2.     Determine the approximate Doppler of each visible satellite.
3.     Search for the signal in both C/A-code delay and frequency (i.e., Doppler shift).
4.     Detect a signal and determine its code delay and carrier frequency.
5.     Track the C/A-code delay and carrier frequency as they change.

Signal Acquisition
The acquisition process consists of Steps 1–4 in the foregoing list. In Steps 1 and 2 the visible satellites and approximate Doppler shifts are usually found using approximate time, approximate receiver position, and almanac data (for satellite position and velocity) — all of which have been previously stored in the receiver. This permits the receiver to establish a frequency search region for each visible satellite, and is similar to establishing the region of ocean to search in the above analogy.

Step 3 requires by far the most computation. The C/A-code search is necessary because GPS signals are spread-spectrum signals in which the C/A code spreads the total signal power over a wide bandwidth, dropping its power density well below that of a receiver’s thermal noise. A signal is therefore virtually undetectable unless it is de-spread to a much narrower bandwidth by correlation with a replica code in the receiver that is precisely time-aligned with the received code.

Because the signal cannot be detected until alignment has been achieved, a search over all possible alignment positions is required. For each trial code alignment position, the signal must be averaged over a sufficiently long time period to build up the signal-to-noise ratio (SNR) to a usable level.

Such averaging requires that the receiver be accurately tuned to the received carrier frequency; otherwise the averaging can be severely degraded. However, at L-band the frequency uncertainty of a typical receiver’s reference oscillators and the Doppler uncertainty due to uncertainty in receiver location and velocity can make the tuning uncertainty as large as several kilohertz (satellite motion alone account for approximately ±5 kilohertz at L1). Thus, in addition to the code search, a receiver also needs to search in frequency.

. . .

Signal Tracking
Once the cell containing the signal has been detected in Step 4, typical receivers use code and carrier tracking loops in Step 5 to generate error signals that keep the replica and received codes aligned and also keep the receiver tuned to the correct frequency as changes in Doppler occur. However, a discrete approximation to these methods of tracking is to repeatedly compare the values of S in the current signal cell with the values in the eight cells surrounding it.

Although the approximation is somewhat crude, it makes analysis of tracking sensitivity much easier and does not really falsify our understanding. If the maximum value of S in the surrounding cells exceeds that of the central cell, the cell with that maximum value is declared as the new signal cell. In this way, both the code delay and carrier frequency of the received signal can be tracked by repeatedly performing a local search over only N = 9 cells, each local search resulting in a tracking update.

. . .

To summarize, with enough processing, no theoretical limit exists for either acquisition or tracking sensitivity. However, because tracking requires examination of only a local code delay and carrier frequency region (and coherent averaging can be used as well over the full length of data bits in legacy L1 GPS signals), tracking can be made more sensitive than acquisition before cost limits (either in hardware or processing time) are reached.

Similar conclusions can be reached for other GNSS signals, even taking into account differences in their characteristics.

(For Lawrence Weill’s complete answer to this question, including formulas and tables, please download the full article using the pdf link above.)

The post Differences between Signal Acquisition and Tracking appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

The use of GNSS for safety critical applications is gaining interest, particularly amongst aviation users, who probably have the most demanding requirements. The GNSS frequency band containing the Galileo E5 and GPS L5 signals is designated as an aeronautical radio navigation service (ARNS) band, which enjoys legal protection from other services not allocated to this frequency on a primary basis.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

The use of GNSS for safety critical applications is gaining interest, particularly amongst aviation users, who probably have the most demanding requirements. The GNSS frequency band containing the Galileo E5 and GPS L5 signals is designated as an aeronautical radio navigation service (ARNS) band, which enjoys legal protection from other services not allocated to this frequency on a primary basis.

However, GNSSes do not hold exclusive rights to this frequency, and its use of the frequency on a primary basis may expose a GNSS signal to potential interference from other services that enjoy similar emission rights, affecting performance in safety critical applications.

These other services include pulsed interference originating from systems such as distance measuring equipment (DME), Tactical Air Navigation (TACAN) signals, and the Joint Tactical Information Distribution System (JTIDS), as well as military radars that may cause significant service degradation. Moreover, in addition to the severe effects on the E5/L5 band by induced interference, the situation becomes even more problematical when these signals are used in conjunction with the Galileo E6 frequency band.

Not only pulsed interference, but also other RF transmissions such as continuous wave (CW) signals can degrade the reception of GNSS signals. An example of such interference occurs due to the harmonics originating from the European digital video broadcast terrestrial (DVB-T) service, which can appear in RNSS frequency bands.

Interference can be mitigated through various means. On the hardware side, specialized instrumentation such as choke rings or active beam-forming antennas, suppress interference and improve the reception of line-of-sight satellite signals. Special RF front-end architectures make use of pulse blanker and/or automatic gain control (AGC) to reduce RFI. With respect to a GNSS receiver’s digital signal processor (DSP), performance degradation due to interference can be treated in the receiver’s software, using interference mitigation algorithms.

In this column, we will focus on the DSP solutions, although we need to emphasize that in order to achieve the best results, all three elements of a generic GNSS receiver antenna, RF front-end, and DSP — must be considered, while measures taken for any individual element need to be coordinated with the others.

Interference Mitigation by Means of Wavelet
Pulse blanking is the most common approach to suppress pulsed interference. However, some traditional pulse blanking designs are based on monitoring the automatic gain control (AGC) within the receiver’s front-end and activating the blanking at instances when an abrupt and significant increase of the AGC is reported. Due to the limited dynamics of the AGC, pulse blanking suffers is less effective in cases where high pulse repetition frequencies occur.

The wavelet based technique described in detail by C. Burrus et alia in the publication cited in the Additional Resources section near the end of this article is not based on AGC techniques. Thus, it is not only suited for high power pulses but also for medium to low power pulses, as we will demonstrate later on. Further benefits of the wavelet approach to interference mitigation for pulsed interference are explained in the article by E. Anyaegbu et alia (see Additional Resources) in the frame of GNSS signal processing.

The traditional Fourier series and fast Fourier transformation (FFT) are based on sinusoidal functions with infinite support. Although applying this transformation gives complete insight into the signal’s frequency evolution, it removes all time-dependent information that we might want to analyze.

An analysis of pulsed interference requires both a time and frequency representation of the signal. To achieve this end, we could cut the signal into several time-dependent sections and then analyze each independently. However, we still need to determine the instant in time to cut the signal, while identifying all frequency components at a certain time instance.

In order to meet this desire, we cut the signal using a Dirac pulse and then transform the result to the frequency domain. The cutting of the signal corresponds to a convolution in the time domain and thus to a multiplication in the frequency domain. Finally, a Fourier transform of the Dirac pulse contains all possible frequencies and consequently the frequency information of the initial signal is smeared out to all frequencies.

This concept is an analogous to Heisenberg’s uncertainty relation as — in signal processing terms — it is impossible to know the exact frequency and the exact time resolution of a signal. The key to analyzing pulsed interference can be seen in the selection of the correct cutting of the signal.

With wavelet analysis we overcome this problem by selecting the time at which to cut the signal using a flexible and scalable window function. We shift the window along the time axis for every point in time the spectrum is calculated, which can be repeated several times using slightly compressed window functions.

The final result is a time-frequency representation of the signal. In the wavelet analysis the frequency term is mostly replaced, as explained later, by a scaling operation to have a clear boundary to the Fourier transformation.

Continuous Wavelet Transformation
. . . The wavelet functions are deduced from one single wavelet, the so-called mother wavelet ψ(t), by scaling and translation . . . These formulas are not linked to a unique and single function ψ(t) as with the case for the Fourier transformation. We declare functions for which a number of characteristic properties hold as “mother wavelets.” We invite interested readers to consult Burrus et alia for a further explanation of wavelet mother functions.

Discrete Wavelet Transformation
Working with sampled data requires the definition of a discrete Wavelet Transformation…Discrete wavelets require an infinite number of scalings and translations in order to be able to fully represent the original input function. Although a break-off of the wavelet series may offer a way out, the truncation error still needs to be controlled.

From the defining characteristics of a wavelet function, we suggest that Wavelet functions offer a band-pass–like spectrum, where a compression in time can also be expressed as a stretch in the frequency domain together with a shifting up to higher frequencies.

We use this characteristic to construct a series of wavelets covering the whole frequency range of our input signal, where special attention needs to be paid so that each stretched wavelet spectra touch its neighbors as shown in Figure 1 (see inset photo, above right).

In practice, it is impossible to cover all spectrum of an input function down to zero. The most elegant solution resulting in applicable wavelets is to stop stretching the wavelet once the open hole is small enough and then fill it with a so-called scaling function.

. . .

Pulsed Interference Mitigation by Wavelets
Now that we have defined the prerequisites for Wavelet analyses, we would like to return to our original approach to identifying and mitigating medium to low pulsed interference by means of wavelets.

. . .

Step 1  — Discrete Wavelet Transformation. The first step towards correctly identifying pulsed interference uses a discrete wavelet transformation, with a complete manifold of potential wavelet mother functions. For the best results — that is, those yielding both the highest correlation between the pulsed interference and the wavelet, as well as the lowest correlation between the wavelet function and the GNSS plus noise signal — an optimization could be carried out …

Step 2 – Exact Pulse Position in Time. With appropriate knowledge of the expected pulse duration, a constant windowing function g(t) is generated and correlated with the approximate scale coefficients. This determines the correct time location of the pulse within the IF samples … where an easily distinguishable local maximum is obtained in the pulse-present case …

Step 3 – Pulsed Interference Excision. After correct identification of the pulse in the time domain, we perform a pulse excision by modifying the affected approximate and detailed scale coefficients, cA and cD. After comparing potential solutions by modifying the scale coefficients, the classical blanking approach still shows best performance.

Step 4 – Inverse Discrete Wavelet Transformation. In the final step, we apply an inverse discrete wavelet transformation in order to regain the original IF samples after eliminating the samples affected by pulsed interference.

Low Power DME Interference Mitigation
Distance measuring equipment employs a transponder-based radio navigation technology that measures distance by timing the propagation delay of radio signals. DME pulsed interference is to be expected in the 1151–1213 megahertz frequency range when operating in X mode, thus affecting the E5/L5 band.

. . . While the wavelet-based interference mitigation approach has been outlined earlier for high-power pulses, here, we assess the performance of these algorithms for the case of low-power interference. We use a standard pulse interval of 12 microseconds between the two DME single pulses, while we consider a repetition rate of about 2,700 pulse pairs per second (pps) at the upper limit of the DME specifications.

. . .

Performance Assessment of Wavelet-Based Interference Mitigation
Now that we have demonstrated the capability of wavelet techniques to detect interference, we will apply the mitigation approach and assess its performance. We evaluate the mitigation approach, for both the case of the high-power pulsed interference scenario as well as for low-power DME pulsed interference.

. . .

Wavelet-Based Interference Mitigation vs. Pulse Blanking
We compared the benefits and drawbacks of the well-established time domain pulse blanking technique with the wavelet-based approach for mitigating pulsed interference.

. . .

Summary of Wavelet-Based Interference Mitigation
We consider signal analysis by means of wavelets as an innovative technique, providing not only insight into the frequency content of the signal as with the traditional Fourier analysis but also enabling signal analysis in the time domain.

. . .

Notch Filtering for CW Interference Mitigation
The design of interference mitigation algorithms applicable to continuous wave (CW) interference focuses on suppression of the high spectral peaks related to the interferer.

. . .

Performance Assessment of Notch Filtering–Based Mitigation Technique
… After applying the notch filter, the spectral peaks originating from the CW interference were well suppressed. The resulting PSD is almost identical to the one without any interference.

. . .

Conclusion and Future Developments
We have outlined two different interference mitigation approaches, applied to the digital part of GNSS receivers. Wavelet-based pulsed interference mitigation shows a significant potential for future use for both high- and low-power pulses, enabling accurate detection and mitigation. Significant performance improvements are measured at both the C/N₀ level and tracking loop level have been reported for high power pulsed interference.

Additionally, our analysis of notch filtering against CW interference threats indicates significant capabilities as well.

We should underline that all algorithms have been implemented in the IpexSR software receiver, enabling interference mitigation in a post-processing laboratory environment. Currently, implementation of the wavelet-based interference mitigation approach for real-time applications in particular is being pursued at the University FAF Munich Institute of Geodesy and Navigation.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

Acknowledgment
The results shown in this paper have been accomplished at the Institute of Geodesy and Navigation of the University FAF Munich within ESA contract No. 21095/07/NL/HE.

Additional Resources
[1] Anyaegbu, E., and G. Brodin, J, Cooper, E, Aguado, and S. Boussakta, “An Integrated Pulsed Interference Mitigation for GNSS Receivers,” Journal of Navigation, The Royal Institute of Navigation, Cambridge University Press, Volume 61, Issue 2, 2008
[2] Burrus, C.S., and R. A. Gopinath and H. Guo, Introduction to Wavelets and Wavelet Transforms: A Primer, Prentice Hall, Upper Saddle River, New Jersey, USA, 1998
[3] ICAO NSP WG1&2/WP5: Interference Susceptibilities of Aeronautical Systems Operating in the 960-1215 MHz Band, 2005
[4] Steingass, A., and A. Hornbostel and H. Denks, “Airborne Measurements of DME Interferers at the European Hotspot,” Proceedings of European Navigation Conference ENC/GNSS 2009, Naples, Italy, May 04, 2009
[5] Stöber, C., and M. Anghileri, A. Sicramaz Ayaz, D. Dötterböck, I. Krämer, V. Kropp, J.H. Won, B. Eissfeller, D. Sandromà Güixens, and T. Pany, “IpexSR: A Real-Time Multi-Frequency Software GNSS Receiver,” Proceedings of IEEE ELMAR 2010, Zadar, Croatia

The post Wavelets and Notch Filtering appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Galileo receiver designers require formal interface specifications for the Galileo signal-in-space (SIS) in order to write unambiguous and accurate specifications for Galileo receivers. To compute their positions, Galileo receivers must be able to retrieve timing and orbital information from the data stream conveyed in Galileo analog signals.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

Galileo receiver designers require formal interface specifications for the Galileo signal-in-space (SIS) in order to write unambiguous and accurate specifications for Galileo receivers. To compute their positions, Galileo receivers must be able to retrieve timing and orbital information from the data stream conveyed in Galileo analog signals.

Next to the algorithms and the numerical issues, the correctness of the position solution also depends on the semantically correct interpretation of the data items in terms of their syntax and semantics. Multi-GNSS receivers are particularly challenged as these combine data from multiple and diverse formats in order to calculate the position solutions.

For example, an orbital eccentricity parameter can be represented in several binary and numerical formats. In order to reduce possible misunderstandings between Galileo designers and designers of other types of GNSS receivers, and also to minimize the risk of incorrectly computing a position solution, the Galileo interface specification must be clear, with all ambiguities and inconsistencies eliminated.

Misinterpretation of design specifications is not a new problem in the wider field of engineering. In the system engineering community, these problems are addressed by formalized approaches such as Model-based System Engineering (MBSE), which require design documents to use formal and graphical languages.

The intent of an MBSE approach is to overcome the inherent ambiguities of natural language-based specification documents. MSBE approaches are used not only to support design specifications, but also to support all the phases of system design and life cycle, including intermediate verifications and final system validation.

In this article, we aim to overcome the limitations of the current GNSS SIS interface specification by proposing an MBSE approach for the Galileo SIS Interface Control Document (ICD), which is currently available in a textual format.

To overcome the limitations of the current GNSS SIS interface specifications, we propose use of the Interface Communication Modelling Language (ICML), a modelling language that enables GNSS designers to formally and graphically specify SIS interfaces, as an alternative to the conventional text used to prepare ICDs.

As a consequence of the increased level of formality, we expect to see an improvement in the design processes of GNSS-based systems, including enhanced communication among stakeholders, reduced design times, and reduced design risks.

In addition, ICML can also lead to the automatic generation of software conversion routines; specification consistency and completeness checking to ensure the correctness of the interface specifications and their consistency with lower-level design specifications; generation of designer friendly and interactive documentation in various formats, including web-based ones; and multi-GNSS interoperability on the receiver side.

An important note: Although no plans have been made to release the Galileo ICD using ICML, in this study we evaluate ICML features that could be particularly valuable for Galileo.

ICML is based on the standard and widely known Unified Modelling Language (UML) and Business Process (BP). This allows us to leverage existing UML and BP modelling tools, thereby gaining advantages from their wide availability and related standards. These system engineering tools also include Object Constraint Language (OCL) for specifying constraints on models, and SysML, system modelling language.

In this article, we first will outline the concepts of MBSE and UML and discuss the advantages that Galileo would obtain from a formal SIS specification in ICML. We then examine the structure of ICML specifications and provide an example ICML specification for a simplified and facsimile Galileo F/NAV message, which is the designated navigation message format for the Open Service on the E5a frequency.

Model-Based System Engineering (MBSE)
Traditionally, the design of a complex system relies on a system engineering process that uses on text documents and engineering data in multiple formats from different disciplines. This information is generally developed and shared electronically among all the relevant system stakeholders.

Much of the system engineering effort is spent to ensure that information is consistent across disciplines and maintained throughout the various versions of the document produced while advancing the system design. To assist in this, a system engineering management plan (SEMP) document specifies how the entire engineering process develops, including which documents need to be produced and what their inter-relationships are.

Due to its inherent nature, the document-based approach presents fundamental limitations, deriving from manual operation of support activities, dispersed data, and unstructured representation of information. Jointly, these factors affect the traceability of requirements across documents and throughout the design process — affecting design specification consistency and completeness, and thus representing a source of risk for development of the system.

All these problems are further exacerbated when the system under design involves integration of two or more systems, especially in cases where the systems are independently designed. In addition to increased engineering complexity due to the larger number of systems, the communication interfaces become a critical aspect of the entire process.

INCOSE, the International Council on System Engineering, defines MBSE as “the formalized application of modelling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle.”

As such, MBSE aims to overcome the limitations of the conventional document-based approach by leveraging computing tools to structure, share and automatically analyse design information. The ultimate purpose is to ensure specification completeness and consistency, traceability of requirements and design choices, reuse of design patterns and specifications, and a shared understanding of the designs among users and designers.

As a result, the application of MBSE obtains several advantages, presented here with examples of the benefits:

• Enhanced communications: Enabling a shared understanding of the system across the development team and with other stakeholders, and the ability to integrate views of the system from multiple perspectives.

• Reduced development risk: Providing requirements validation and design verification throughout the process, as well as more accurate cost estimates to develop the system.

• Improved quality: Providing more complete, unambiguous and verifiable requirements; more rigorous traceability between requirements, design, analysis and testing; enhanced design integrity.

• Increased productivity: Analyzing the effects of requirements and design changes more quickly, reusing existing models to support design evolution, reducing errors and time spent on integration and testing, and automating document generation.

• Enhanced knowledge transfer: Standardizing specification and design information so that it can be accessed via query and retrieval software.

MBSE achieves these advantages by building a system model and model repository. A system model is represented digitally and can include information about the system’s specification, design, analysis, and verification.

The model can be produced using a software tool qualitative metrics need to be satisfied by the model for the specific design study, such as model fidelity, model breadth, and model depth. A model repository provides a database of model blocks that can be shared among all the actors involved in the system design, across all the design and development phases.

The software industry has always been at the forefront of the modelling languages, information processing tools and technologies. As a natural consequence, MBSE currently takes advantage of the available modelling languages including UML, BP, and associated tools such as Magic Draw or System Architect along with technologies (e.g., XML), which originated in the software domain and were eventually tailored to the needs of system engineering.

Unified Modelling Language
In this section we outline the basic concept of UML upon which ICML is defined.

UML is a standard graphical modelling language for the representation of structural and behavioural aspects of systems, using the concept of objects. The language consists of a set of diagrams, each defining a set of palettes and a set of relationships that can be used to relate the palettes.

For example, a diagram for the representation of structural aspects is the class diagram. This type of diagram is used to describe classes, or types of objects, in terms of properties and relationships, for general conceptual and detailed modelling.

. . .

ICML Benefits for the Galileo SIS Interface Specification
The Galileo SIS ICD will be used by a large number and variety of receiver designers responsible for defining the specification of Galileo user equipment. New receiver designs may need to reuse and/or modify existing GNSS hardware and software design specifications to conform to Galileo ICD, or solve interoperability issues in existing receivers that use GNSSes.

. . .

ICML Specification
ICML covers both the structural and the implementation aspects of GNSS SIS interface specifications. The structural aspects concern the definition of the data structures. The implementation aspects concern how data values are dealt with.

. . .

Data definition covers the specification of the logical structure of the message data…

The binary coding level covers the specification of the binary data item structures and coding…

Logical binary structure specifies the aggregation of binary sequences in terms of frames, sub-frames, and pages…

The physical binary coding level specifies the partitioning structure for binary sequence segments resulting from digital modulation…

Finally, the physical signal level specifies the structure of analog signals…

. . .

Example Specification for Galileo F/NAV
We will now present a simplified and facsimile Galileo SIS interface specification for the F/NAV message as an example of MBSE applied to GNSS ICDs. For the sake of conciseness, we will illustrate only the ICML specification for the logical binary data and physical binary data levels.

We assume that at the data definition level, the following data items are defined: OMEGADOT and Eccentricity e, as application data, and Page Type Field and CRC (cyclic redundancy check) as control data. The binary coding of these data items can be specified within ICML Level 4, which will also provide the basis for the Level 3 definition of logical binary representation. This representation concerns how Level 4 sequences are combined to form the binary message, including the binary control sequences for start, end, and synchronization.

. . .

Conclusions
Galileo will bring considerable advantages to navigation systems using GNSS, and to the Galileo civilian community, providing independence, increased accuracy, integrity and reliability. Promoting the use of Galileo signals means Galileo receiver designers must be able to accurately specify the Galileo receivers design, derived from the interface with the Galileo SIS.

Specifically, Galileo designers must eliminate Galileo ICD ambiguities and inconsistencies in order to reduce risk, thus making the design and development of Galileo receivers more cost- and time-efficient.

ICML brings a model-based system engineering approach into the specification of GNSS SIS interfaces, thus obtaining numerous advantages, including enhanced communication and reduced design risks. The approach supports a wide number of automatic exploitations (such as checking specification completeness and consistency, document generation, and so forth).

ICML may also be used to identify multi-GNSS interoperability issues on the receiver side involving the retrieval, interpretation, and combination of orbital and timing data from multiple GNSSes for the positioning computation.

Because ICML is based on the UML and BP standard modelling languages originated from the software community, ICML specifications can be created using the plethora of available software tools.

A final caveat: this article represents a preliminary case of study on the suitability of such an approach for the Galileo SIS interface specification and no endorsement is made on the adoption of ICML for Galileo interface.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

Acknowledgements
The authors would like to express their sincere appreciation to Serge Valera of the EGSE and Ground Systems Section, European Space Agency, for his insightful comments.

References
[1] Eriksson, H. E., and M. Penker, B. Lyons, and D. Fado UML 2 Toolkit, Wiley, 2008
[2] Galileo OS SIS ICD Issue 1 Revision 1, September 2010, retrieved from http://ec.europa.eu/enterprise/policies/satnav/galileo/open-service/index_en.htm
[3] Gianni D., and J. Lewis-Bowen, N. Lindman, and J. Fuchs, “Modelling Methodologies in Support of Complex Systems of Systems Design and Integration: Example Applications”, Proceedings of the 4th International Workshop on System & Concurrent Engineering for Space Applications (SECESA2010), Lausanne, Switzerland, October, 2010
[4] Kossiakoff, A., and W. N. Sweet, Systems Engineering Principles and Practice, John Wiley, 2003.
[5] MoDAF Detailed Guidance, http://www.mod.uk/DefenceInternet/AboutDefence/WhatWeDo/InformationManagement/MODAF/ModafDetailedGuidance.htm (last accessed October 2010).
[6] “Model-Based Systems Engineering,” The Journal of the National Council on Systems Engineering (INCOSE), Volume 1, Number 1, 1994, pages 83-92
[7] Object Management Group (OMG) Business Process Model Notation Standard Specification, http://www.omg.org/spec/BPMN
[8] OMG Object Constraint Language Specification, <http://www.omg.org/technology/documents /formal/ocl.htm>
[9] OMG SysML Annex C, Model Library for Quantities, Units, Dimensions and Values (QUDV) www.sysml.org/docs/specs/OMGSysML-v1.2-10-06-02.pdf
[10] OMG SysML Specification, http://www.sysml.org
[11] OMG Unified Modelling Language Standard Specification, http://www.uml.org
[12] OMG XML Metadata Interchange (XMI) Standard Specification, http://www.omg.org/spec/XMI
[13] W3C Extensible Markup Language Specification, http://www.w3.org/XML

The post A Model-Based Approach appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

In satellite navigation, a GNSS receiver must account for several sources of error such as relativistic effects, atmospheric propagation delay, offset of satellite clocks from system time and satellite ephemeris. In order to accurately compute user position, velocity, and time (PVT), these errors need to be predicted/estimated precisely.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

In satellite navigation, a GNSS receiver must account for several sources of error such as relativistic effects, atmospheric propagation delay, offset of satellite clocks from system time and satellite ephemeris. In order to accurately compute user position, velocity, and time (PVT), these errors need to be predicted/estimated precisely.

The navigation signals transmitted on each carrier frequency are imperfectly synchronized due to different hardware paths corresponding to each signal. Each satellite’s navigation message contains parameters describing the timing bias. A user receiver uses these parameters to compute the clock correction for each observation.

Dual-frequency receivers directly employ such corrections. However, before a single frequency receiver can use the computed offset, it must be adjusted to account for the differential group delay between the principal signal and the signal on the other frequency. This timing group delay, annotated as T_GD, results from hardware differences in the onboard signal paths and will vary among satellites.

The dual-frequency signal timing difference is used to infer the line-of-sight delay caused by the ionosphere, subject to the bias difference between the satellite transmissions at the two frequencies. Recently, the satellite navigation community has improved the inter-frequency/signal correction values contained in navigation messages.

This article will describe the timing group delays anticipated in the Indian Regional Navigation Satellite System (IRNSS) and the inter-signal delay correction (ISC) parameters that will be included in the navigation messages in order to improve the system’s PVT accuracy.

GNSS Service Regions
In the future, GNSS systems will have two types of service regions: a terrestrial service volume (TSV) and a space service volume (SSV). The IRNSS ISCs will take into consideration signal differences as they appear in these service regions.

We can characterize the TSV as a shell that begins at the surface of the earth and extends up to an altitude of 3,000 kilometers. The transmitted position-determination parameters are valid for the entire region, ensuring similar performance for all users within it. Users operating in the TSV have coverage from the main beams of the satellites.

The SSV is a shell extending from 3,000-kilometers to approximately the geostationary altitude, that is, around 36,000 kilometers. The SSV is further subdivided into two regions: from 3,000 to 8000 kilometers, and from 8,000 to 36,000 kilometers.

Space users (SU) will have varying levels of performance depending on the altitude. Within the SSV, nearly all navigation signals emanate from satellites across the limb of the Earth. Users within this region may experience periods during which no navigation satellite signals are available and, when they are, received power levels will be weaker than for the terrestrial users (TU). Timing correction for space users need to be provided. Figure 1 (above right) shows the shells of the various service regions.

IRNSS
The Indian Regional Navigation Satellite System envisages establishment of a constellation made up of a combination of geostationary Earth orbit (GEO) and geosynchronous orbit (GSO) spacecraft over the Indian region.

The IRNSS constellation will consist of seven satellites —three in GEO orbit (at 34º E, 83º E and 131.5º E) and four in GSO orbit inclined at 29 degrees to the equatorial plane with their longitude crossings at 55º E and 111.5º E (two in each plane) as shown in Figure 2. All the satellites will be continuously visible in the Indian region for 24 hours a day.

Figure 3 shows a detailed diagram of the IRNSS system configuration.

The IRNSS is expected to provide position accuracy (two sigma) of better than 20 meters over India and a region extending outside the landmass to about 1,500 kilometers. The system will provide two types of services, a Standard Positioning Service hereafter referred to as SPS, and a Restricted/Authorized Service or RS. Both of these services will be provided at two frequencies, one in the L5 band and the other in S-band.

. . .

Timing Group Delay
The time of radiation of the navigation signals on each carrier frequency and among frequencies is not synchronized due to the different digital and analog signal paths that each signal must travel from the IRNSS satellite signal generator to the transmit antenna. This hardware group delay is defined as a time difference between the transmitted RF signal (measured at the phase center of a transmitting antenna) and the signal at the output of the onboard frequency source.

Three different parameters comprise this group delay: a fixed/bias group delay, a differential group delay and a group delay uncertainty in bias and differential value.

. . .

IRNSS Group Delay Parameters
The uploaded data and the onboard-generated data will be formatted in a specific IRNSS format. As code, data, sub-frames, and main frame are synchronized to the space vehicle (SV) time (t_SV), the principal code (RS) epoch is used to generate SV time.

The SV time is measured relative to the leading edge of the first chip of the first code sequence of the first frame symbol and represents the time of transmission of the signal from the satellite. The reference of transmission of signals is the antenna phase center. But, as mentioned earlier, a time delay occurs in the navigation payload between the time of signal generation and its actual time of transmission from the antenna array…

• Estimated Differential Group Delay.

• Group Delay Differential Correction.

. . .

IRNSS Group Delay Correction Algorithm
GNSS receivers designed to process IRNSS signals should account for the group delays, depending on the specific signals used and the service region in which they will operate.

• Single Frequency S-RS and L5-RS Users.

• Single Frequency S-SPS and L5-SPS Users.

• Corrected Pseudo Range For Dual Frequency Users.

. . .

Conclusion
The IRNSS signal structure has one group delay differential correction parameter (T_GD). T_GD is to correct for S- and L5- band RS signal group delays. To obtain better position accuracy, other single-frequency users require inter-signal group delay correction parameters (ISC_L5-SPS, ISC_S-SPS). For space navigation users with off-nadir angles greater than 8.4 degrees with respect to an IRNSS satellite, an SUD correction is required. The SUD bias will provide additional improvement on the order of three nanoseconds to space users. These will be transmitted in navigation data in the future.

For the complete story, including figures, graphs, and images, please download the PDF of the article, above.

Acknowledgments
The authors would like to express their sincere gratitude to Dr K.S. Dasgupta, deputy director of the SATCOM and Navigation Payload Area, Space Applications Centre‑ Indian Space Research Organization (SAC-ISRO), for his valuable guidance and encouragement during this study.

Additional Resources
[1] Hegarty, C., “Accounting for Timing Biases between GPS. Modernized GPS, And Galileo Signals,” 36th Annual Precise Time and Time Interval Meeting, Washington, D.C., December 2004
[2] Parkinson, B. W., and J. J. Spilker Jr., “Global Positioning System: Theory and Applications,” Volume I, Bradford W. Parkinson and James J. Spilker Jr.
[3] Tetewsky, A., and J. Ross, A. Soltz, N. Vaughn, J. Anszperger, C. O’Brien, D. Graham, D. Craig, and J. Lozow, “Making Sense of Inter-Signal corrections: Accounting for GPS Satellite Calibration Parameters in Legacy and Modernized Ionosphere Correction Algorithms,” Inside GNSS, July/August 2009
[4] U.S. Air Force, GPS Directorate, “Interface Specification IS-GPS-200,” Revision D, IRN-200D-001, March 2006
[5] U.S. Air Force, GPS Directorate, IS-GPS-800, Navstar GPS Space Segment/User Segment L1C Interface, August 2007, U.S. Air Force, GPS Directorate
[6] U.S. Air Force, GPS Directorate, Signal in Space Interface Control Document OS SIS ICD, Draft 1, GPS ICD, February 2008
[7] Wilson B., and C. Yinger, W. Feess, and C. Shank, “New and Improved: The Broadcast Interfrequency Biases,” Brian D. Wilson, Colleen H. Yinger and Willian A. Feess, Captain Chris Shank, GPS World, September 1999 

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