Collaborative Navigation: Supporting PNT System Operational Anomaly Detection. Issue 24 (2022)

• Record Type: Journal Article
• Authors: Wang, Xiankun; Toth, Charles; Grejner-Brzezinska, Dorota; Masiero, Andrea
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 24(2022)
• Page Start: 285
• Page End: 291
• Publication Date: 2022
• Subjects: Cooperative navigation -- Localization -- Positioning Systems -- Fault Detection -- Information and sensor fusion; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.10.298
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Modern Positioning, Navigation, and Timing (PNT) systems heavily rely on Global Navigation Satellite Systems (GNSS). Meanwhile, GNSS-based PNT systems are increasingly becoming susceptible to unintentional and deliberate Radio Frequency (RF) interference. In particular, as technology keeps advancing and hardware is becoming so inexpensive, it takes a modest effort to disrupt the normal operation of almost any PNT systems, thus posing an extreme threat to autonomous transportation systems that rely on precise PNT. As communication capabilities are expanding, a group of vehicles can easily share data when they operate in close vicinity. This gives opportunity to position and navigate the vehicles based on a jointly computed navigation solution, which is usually called collaborative navigation, resulting in a potentially more accurate and reliable operation. In this study, the feasibility and performance potential of collaborative navigation on the detection and mitigation of GNSS-based PNT system operational anomalies are evaluated on some real data and simulated anomaly scenarios. By incorporating an outlier detection method based on least squares adjustment, the collaborative navigation has shown to be able to maintain the differences to the reference solution to within 0.2 m, 0.5 m, and 3.0 m for the biased case, noisy case, and anchor case, respectively, for all test vehicles.