TY - GEN
T1 - Spoofing Detection Algorithm for Tightly Coupled INS/GNSS Integration Model with robust Averaging Measurement
AU - Chengyan, He
AU - Luoyu, Wu
AU - Zhang, Zhaolin
AU - Ling, Wang
AU - Mingliang, Tao
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - IGG-III weighting function
KW - Kalman filtering
KW - measurement averaging
KW - robust estimation
KW - Spoofing detection
KW - tightly coupled INS/GNSS
UR - http://www.scopus.com/inward/record.url?scp=85219753146&partnerID=8YFLogxK
U2 - 10.1109/ICSIDP62679.2024.10868403
DO - 10.1109/ICSIDP62679.2024.10868403
M3 - 会议稿件
AN - SCOPUS:85219753146
T3 - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
BT - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
Y2 - 22 November 2024 through 24 November 2024
ER -