Protecting GNSS for Safe Aviation
Detecting interference using machine learning algorithms to monitor ADS-B data.
By Inside GNSSDetecting interference using machine learning algorithms to monitor ADS-B data.
By Inside GNSSThe European Space Agency’s new navigation head, Francisco-Javier Benedicto Ruiz, has a lot to say about GNSS, both present and future. We recently spoke with him about his views on satellite navigation, signal vulnerability and authentication, and the agency’s working relationship, or not, with Russia. The technical team behind the Galileo authentication service and industry representatives developing alternative positioning, navigation and timing solutions also share insights.
By Peter GutierrezAs guest columnist Dino Smajlovic explains, testing allows for inertial error characterization and understanding, ensuring proper error budgets and more accurate navigation solutions. Rate tables are among the tools used, with some allowing testing, characterizing and modeling in one installation step.
By Inside GNSSRTCA is working to develop new standards to tackle GNSS growth and challenges. Here’s an update on the special committee’s progress, provided during a recent webinar.
By Dawn M.K. Zoldi (Colonel, USAF, Ret.)Errors in inertial sensor measurements are accumulated over time, leading to drift in INS navigation outputs. While gyro bias is the main contributor, other factors, such as accelerometer bias and noise, are important to consider for balancing the overall error budget.
By Andrey SolovievRobustness to GPS jamming and spoofing is critical for military applications yet challenging, and numerous alternative sensing techniques have been explored over the years. Virtual aiding methods have proven effective, with the ability to constrain and localize the search space for improved operability in GPS-denied environments.
By Inside GNSSA: GNSS users who must verify the integrity of their navigation solutions to meet safety requirements need at least some knowledge of the degree to which they can trust the signals received from GNSS satellites before additional monitoring is added.
By Inside GNSSThe SAGAIE network was deployed in West-Africa in 2013 to assess the feasibility of an equatorial for ASECNA SBAS by studying ionospheric scintillation. This study of the network’s measurements, taken between 2013 and 2016, analyzes the characteristics of the scintillation recorded by five receivers that cover Sub-Saharan West-Africa.
By Inside GNSSThis research derives effective formulas relating GNSS meta-signal observations to the measurements obtained from its side-band components, when processed independently in a standard receiver architecture. Meta-signal processing can lead to high-accuracy solutions even under harsh conditions.
By Inside GNSSIn this second column we consider fundamental principles of inertial navigation that derive position, velocity and angular orientation from measurements of accelerometers and gyroscopes.
By Andrey SolovievThe European Geostationary Navigation Overlay Service (EGNOS) will soon launch a new maritime solution that will make legacy and costly coastal ground-based augmentation systems redundant. Meanwhile, the next generation EGNOS V3, featuring dual-frequency, multi-constellation (DFMC) services, is set to come online by 2028, once GPS L5 is declared operational.
By Peter GutierrezA novel method for improving the positioning accuracy of GNSS receivers exploits a machine learning (ML) algorithm. The ML model uses the post-fit residuals, which are readily available after the position computation from the position, velocity and timing (PVT) engine, adoptable by existing receivers without requiring any modification. The performance of this method, demonstrated using data collected with mass-market receivers as well as a Google public dataset collected with Android smartphones, shows the practicality of the concept.
By Inside GNSSInside GNSS’s resident inertial expert examines coasting over GNSS outages, navigation in challenged environments and interference mitigation in a sensor-fusion environment.
By Andrey Soloviev