Tightly Coupled GNSS/INS Integration Spoofing Detection Algorithm Based on Innovation Rate Optimization and Robust Estimation

The spoofing detection algorithm for a global navigation satellite system/inertial navigation system (GNSS/INS) integrated navigation system based on the innovation rate and robust estimation has limitations such as extensive or invalid detection times, high missed detection rates, and false alarm r...

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Bibliographic Details
Published in:IEEE access Vol. 10; pp. 72444 - 72457
Main Authors: Ke, Ye, Lv, Zhiwei, Zhang, Chao, Deng, Xu, Zhou, Wenlong, Song, Debiao
Format: Journal Article
Language:English
Published: Piscataway IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Covariance matrices
Detection algorithms
Estimation
False alarms
Global navigation satellite system
Inertial navigation
Innovation rate optimization
Innovations
Interference
Navigation systems
Optimization
Receivers
robust estimation
Robustness
Spoofing
spoofing detection
Statistical tests
Technological innovation
tightly coupled GNSS/INS integration
Unmanned aerial vehicles
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:The spoofing detection algorithm for a global navigation satellite system/inertial navigation system (GNSS/INS) integrated navigation system based on the innovation rate and robust estimation has limitations such as extensive or invalid detection times, high missed detection rates, and false alarm rates. This study addresses these limitations by proposing a tightly coupled GNSS/INS integration spoofing detection algorithm based on innovation rate optimization and robust estimation. The proposed algorithm improved the normalized innovation of a small step or slow-growing ramp, thereby optimizing its innovation rate test statistics. The proposed approach also reduces the spoofing effect on the innovation rate by adaptively adjusting a gain matrix using robust estimation, thus improving the detection ability further. The simulation results show that the detection time of the proposed algorithm is reduced by 51.9% on average when dealing with small step or slow-growing ramp spoofing. Moreover, the missed detection rate decreases by 58% on average, and the false alarm rate remains at approximately zero. The proposed algorithm is suitable for spoofing detection in unmanned aerial vehicle applications of GNSS/INS integrated navigation systems with the advantages of fast detection and good performance.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2022.3186305