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 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.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icsidp62679.2024.10868403
Primary Topic
GNSS positioning and interference
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Zhaolin Zhang, Chengyan He, Ling Wang, Wu Luoyu et al.
GNSS positioning and interference
article

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

Zhaolin Zhang, Chengyan He, Ling Wang, Wu Luoyu, Tao Mingliang
article en

Abstract

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.

Northwestern Polytechnical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 55%
GNSS positioning and interference
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