Tightly-coupled GNSS/INS spoofing detection algorithm for LS-SVM and robust estimation

被引：0
|
作者：
Ke Y. [1 ,2 ]
Lyu Z. [1 ]
Zhou W. [1 ]
Deng X. [1 ]
Shang X. [1 ,3 ]
Wu W. [1 ]
机构：
[1] School of Geospatial Information, PLA Strategic Support Force Information Engineering University, Zhengzhou
[2] 31618 of the PLA, Fuzhou
[3] Key Laboratory of Electro-Optical Countermeasures Test & Evaluation Technology, Luoyang
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2024年 / 50卷 / 01期
基金：
中国国家自然科学基金;
关键词：
least squares-support vector machine; ramped; robust estimation; spoofing detection; tightly-coupled GNSS/INS;
D O I：
10.13700/j.bh.1001-5965.2022.0231
中图分类号：
学科分类号：
摘要：
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. © 2024 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
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页码：299 / 307
页数：8
相关论文
共 22 条
  • [1] BIAN S F, HU Y F, JI B., Research status and prospect of GNSS anti-spoofing technology, Scientia Sinica (Informationis), 47, 3, pp. 275-287, (2017)
  • [2] LIU Y, LI S H, FU Q W, Et al., Analysis of Kalman filter innovation-based GNSS spoofing detection method for INS/GNSS integrated navigation system, IEEE Sensors Journal, 19, 13, pp. 5167-5178, (2019)
  • [3] ZHANG C, LYU Z W, ZHANG L D, Et al., A spoofing detection algorithm for INS/GNSS integrated navigation system based on innovation rate and robust estimation, Journal of Chinese Inertial Technology, 29, 3, pp. 328-333, (2021)
  • [4] ZHANG L Y, ZHAO H B, SUN C, Et al., Enhanced GNSS spoofing detector via multiple-epoch inertial navigation sensor prediction in a tightly-coupled system, IEEE Sensors Journal, 22, 9, pp. 8633-8647, (2022)
  • [5] BRUMBACK B, SRINATH M., A Chi-square test for fault-detection in Kalman filters, IEEE Transactions on Automatic Control, 32, 6, pp. 552-554, (1987)
  • [6] LIU H Y, ZHENG G, WANG H N, Et al., Research on integrity monitoring for integrated GNSS/SINS system, The 2010 IEEE International Conference on Information and Automation, pp. 1990-1995, (2010)
  • [7] LI X, FANG K, LI X, Et al., Fault identification method of GNSS/INS integrated navigation system based on the fusion of chi-square test and multiple solution separation algorithm, China Satellite Navigation Conference Proceedings, pp. 558-569, (2021)
  • [8] LIU Y, LI S H, FU Q W, Et al., Impact assessment of GNSS spoofing attacks on INS/GNSS integrated navigation system, Sensors, 18, 5, (2018)
  • [9] ZHONG L N, LIU J Y, LI R B, Et al., Approach for detecting soft faults in GPS/INS integrated navigation based on LS-SVM and AIME, Journal of Navigation, 70, 3, pp. 561-579, (2017)
  • [10] KE Y, LYU Z W, ZHOU W L, Et al., Innovation optimal robust estimation spoofing detection algorithm of tightly coupled GNSS/INS integration, Journal of Chinese Inertial Technology, 30, 2, pp. 272-280, (2022)
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