| Citation: | KE Y，LYU Z W，ZHOU W L，et al. Tightly-coupled GNSS/INS spoofing detection algorithm for LS-SVM and robust estimation[J]. Journal of Beijing University of Aeronautics and Astronautics，2024，50（1）：299-307 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0231
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The traditional spoofing detection algorithm suffers from a prolonged time of detecting ramp spoofing with small slopes, a high false alarm rate, and a high missed detection rate. Therefore, this study proposes a spoofing detection algorithm with tightly-coupled global navigation satellite system (GNSS) and inertial navigation system (INS) based on least squares-support vector machine (LS-SVM) and robust estimation. The algorithm effectively mitigates the influence of spoofing on innovation by adaptively adjusting the gain matrix with robustness. It then replaces the spoofing innovation in the filter with the forecasted innovation obtained by LS-SVM regression of the training data set optimized with robustness, thus further improving the detection and processing ability of ramp spoofing with small slopes. Simulation results show that when detecting 0.1 m/s ramp spoofing, the proposed algorithm can shorten the detection time by 26.65%, reduce the false alarm rate by 40.63% and improve the positioning accuracy by 72.72%, compared with the traditional algorithm. The proposed algorithm has the advantages of fast detection and low false alarm rate, suitable for ramp spoofing detection of tightly integrated GNSS/INS navigation users.
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