Spoofing Detection Algorithm for Tightly Coupled INS/GNSS Integration Model with robust Averaging Measurement

Global Navigation Satellite Systems (GNSS) are susceptible to external signal interference.The GNSS-INS tightly coupled model exhibits high robustness and can avoid some interference; however, it is ineffective against spoofing interference, especially slow-changing spoofing interference. This paper...

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Vydáno v:2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP) s. 1 - 6
Hlavní autoři: Chengyan, He, Luoyu, Wu, Zhang, Zhaolin, Ling, Wang, Mingliang, Tao
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 22.11.2024
Témata:
Detection algorithms
Global navigation satellite system
IGG-III weighting function
Interference
Kalman filtering
measurement averaging
Noise measurement
Particle measurements
robust estimation
Robustness
Simulation
Spoofing detection
Technological innovation
tightly coupled INS/GNSS
Weight measurement
White noise
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Shrnutí:Global Navigation Satellite Systems (GNSS) are susceptible to external signal interference.The GNSS-INS tightly coupled model exhibits high robustness and can avoid some interference; however, it is ineffective against spoofing interference, especially slow-changing spoofing interference. This paper proposes a robust detection algorithm based on measurement averaging and the IGG-III weighting function to effectively identify and mitigate such interference. By constructing a detection statistic from the measurement-averaged innovation, we theoretically demonstrate its nature as a zero-mean white noise process and design a corresponding adaptive detection strategy. Compared with traditional spoofing interference detection methods, simulation experiments using an open-source dataset show that the proposed algorithm significantly improves the detection rate of slowly varying spoofing signals while maintaining a low false alarm rate, validating its effectiveness and robustness in tightly coupled INS/GNSS systems.
DOI:10.1109/ICSIDP62679.2024.10868403