留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于开/闭环交替的GNSS/INS一致性欺骗检测技术

程予洋 彭新智 封帆 徐奕禹 袁雪林 朱祥维

程予洋, 彭新智, 封帆, 徐奕禹, 袁雪林, 朱祥维. 基于开/闭环交替的GNSS/INS一致性欺骗检测技术[J]. 全球定位系统, 2024, 49(4): 48-55, 65. doi: 10.12265/j.gnss.2024020
引用本文: 程予洋, 彭新智, 封帆, 徐奕禹, 袁雪林, 朱祥维. 基于开/闭环交替的GNSS/INS一致性欺骗检测技术[J]. 全球定位系统, 2024, 49(4): 48-55, 65. doi: 10.12265/j.gnss.2024020
CHENG Yuyang, PENG Xinzhi, FENG Fan, XU Yiyu, YUAN Xuelin, ZHU Xiangwei. Consistency deception detection technique for GNSS/INS based on open-closed-loop alternation[J]. GNSS World of China, 2024, 49(4): 48-55, 65. doi: 10.12265/j.gnss.2024020
Citation: CHENG Yuyang, PENG Xinzhi, FENG Fan, XU Yiyu, YUAN Xuelin, ZHU Xiangwei. Consistency deception detection technique for GNSS/INS based on open-closed-loop alternation[J]. GNSS World of China, 2024, 49(4): 48-55, 65. doi: 10.12265/j.gnss.2024020

基于开/闭环交替的GNSS/INS一致性欺骗检测技术

doi: 10.12265/j.gnss.2024020
详细信息
    作者简介:

    程予洋:(2001—),女,硕士研究生,主要研究方向为卫星导航欺骗干扰检测. E-mail:chengyy28@mail2.sysu.edu.cn

    彭新智:(1996—),男,博士研究生,主要研究方向为智能感知可信导航. E-mail:pengxzh9@mail2.sysu.edu.cn

    封帆:(1996—),男,博士研究生,主要研究方向为卫星导航欺骗干扰检测. E-mail:fengf37@mail2.sysu.edu.cn

    徐奕禹:(1998—),男,硕士研究生,主要研究方向为导航安全、卫星导航欺骗干扰检测. E-mail:xuyy53@mail2.sysu.edu.cn

    袁雪林:(1979—),男,副教授,博士,主要研究方向为导航安全、UWB 精密测量与室内定位. E-mail:yuanxlin3@mail.sysu.edu.cn

    朱祥维:(1980—),男,教授,博士,研究方向为北斗系统和综合定位导航授时(PNT)体系. E-mail:zhuxw666@mail.sysu.edu.cn

    通信作者:

    朱祥维 E-mail: zhuxw666@mail.sysu.edu.cn

  • 中图分类号: P228.4

Consistency deception detection technique for GNSS/INS based on open-closed-loop alternation

  • 摘要: GNSS与惯性导航系统(inertial navigation system,INS)在车辆、无人机等领域广泛应用,但GNSS接收机容易受到欺骗信号影响,因此本文提出一种利用INS观测量的一致性欺骗检测技术. 惯性器件有着不易受欺骗信号干扰和易产生累计误差的特性,通过开/闭环交替反馈估计误差来构建GNSS/INS组合导航,在开环期间设置欺骗检测窗口,将惯性器件和GNSS得到的加速度、角速度统计检测量进行一致性检测,判断是否存在欺骗. 实验结果证明:当窗口时间为70 s时,检测概率达到99.2%,虚警概率为5.2%.

     

  • 图  1  欺骗检测系统框架图

    图  2  一致性检测前的数据处理流程

    图  3  欺骗检测窗口期循环流程图

    图  4  The Litton LN-200 IMU

    图  5  模拟在有、无欺骗下的两个车辆轨迹

    图  6  加速度决策统计量的概率密度

    图  7  角速度决策统计量的概率密度

    图  8  组合决策统计量的概率密度($ \lambda = 0.75 $)

    图  9  不同窗口宽度、样本数下的虚警率

    图  10  不同分配权值$ \lambda $下的决策统计量变化曲线

    图  11  开/闭环交错下的车辆轨迹模拟图

    图  12  混淆矩阵

    表  1  LN-200 IMU参数

    参考 加速度计 陀螺仪
    零偏标准差 $ 0.3\; {\text{mg}} $ $ 1.0 (^\circ ){\text{/h}} $
    低通滤波时间常数 100 s 300 s
    随机游走系数 $ 0.02 \;{\text{m/}}{{\text{s}}^{\text{2}}}{\text{/}}\sqrt {{\text{Hz}}} $ $ 0.05 \;{\text{rad/s/}}\sqrt {{\text{Hz}}} $
    下载: 导出CSV

    表  2  二元检测表

    预测真实$ {H_0} $$ {H_1} $
    $ {H_0} $TNFP
    $ {H_1} $FNTP
    下载: 导出CSV
  • [1] BOGUSPAYEV N, AKHMEDOV D, RASKALIYEV A, et al. A comprehensive review of GNSS/INS integration techniques for land and air vehicle applications[J]. Applied sciences, 2023, 13(8): 4819. DOI: 10.3390/app13084819
    [2] GAO Y J, LV Z W, ZHANG L D. Two-step trajectory spoofing algorithm for loosely coupled GNSS/IMU and NIS sequence detection[J]. IEEE access, 2019(7): 96359-96371. DOI: 10.1109/ACCESS.2019.2927539
    [3] CHEN C, CHANG G. Low-cost GNSS/INS integration for enhanced land vehicle performance[J]. Measurement science and technology, 2019, 31(3): 035009. DOI: 10.1088/1361-6501/ab52cb
    [4] GROVES P. Principles of GNSS, inertial, and multi-sensor integrated navigation systems[M]. Engineering, Computer Science, Physics, 2007.
    [5] FALCO G, PINI M, MARUCCO G. Loose and tight GNSS/INS integrations: comparison of performance assessed in real urban scenarios[J]. Sensors, 2017, 17(2): 255. DOI: 10.3390/s17020255
    [6] 李松, 唐小妹, 孙鹏跃, 等. GNSS/INS紧组合最大熵卡尔曼滤波算法[J]. 全球定位系统, 2020, 45(4): 1-8.
    [7] HE Y, LI J C, LIU J J. Research on GNSS INS & GNSS/INS integrated navigation method for autonomous vehicles: a survey[J]. IEEE access, 2023(11): 79033-79055. DOI: 10.1109/ACCESS.2023.3299290
    [8] WU Y, CHEN S, YIN T. GNSS/INS tightly coupled navigation with robust adaptive extended Kalman filter[J]. International journal of automotive technology, 2022, 23(6): 1639-1649. DOI: 10.1007/s12239-022-0142-7
    [9] 倪少杰, 李诗扬, 谢郁辰, 等. GNSS/INS超紧组合导航综述[J]. 国防科技大学学报, 2023, 45(5): 48-59. DOI: 10.11887/j.cn.202305006
    [10] CURRAN J T, BROUMENDAN A. On the use of low-cost IMUs for GNSS spoofing detection in vehicular applications[C]//Proceedings of International Technical Symposium on Navigation and Timing, 2017: 1-8.
    [11] BROUMANDAN A, LACHAPELLE G. Spoofing detection using GNSS/INS/Odometer coupling for vehicular navigation[J]. Sensors, 2018, 18(5): 1305. DOI: 10.3390/s18051305
    [12] CECCATO M, FORMAGGIO F, LAURENTI N, et al. Generalized likelihood ratio test for GNSS spoofing detection in devices with IMU[J]. IEEE transactions on information forensics and security, 2021(16): 3496-3509. DOI: 10.1109/TIFS.2021.3083414
    [13] LO S, CHEN Y H, REID T, et al. Keynote: The benefits of low cost accelerometers for GNSS anti-spoofing[C]//Proceedings of the ION 2017 Pacific PNT Meeting. 2017: 775-796.https://doi.org/10.33012/2017.15109
    [14] DONG Y, WANG D, ZHANG L, et al. Tightly coupled GNSS/INS integration with robust sequential Kalman filter for accurate vehicular navigation[J]. Sensors, 2020, 20(2): 561. DOI: 10.3390/s20020561
    [15] 刘东亮, 成芳, 沈朋礼, 等. LSTM辅助车载GNSS/INS组合导航算法及性能分析[J]. 全球定位系统, 2023, 48(5): 21-31. DOI: 10.12265/j.gnss.2023111
    [16] LIU Y, LI S H, FU Q W, et al. Impact assessment of GNSS spoofing attacks on INS/GNSS integrated navigation system[J]. Sensors, 2018, 18(5): 1433. DOI: 10.3390/s18051433
    [17] XU R, DING M Y, QI Y, et al. Performance analysis of GNSS/INS loosely coupled integration systems under spoofing attacks[J]. Sensors, 2018, 18(12): 4108. DOI: 10.3390/s18124108
    [18] 吴晓倩, 卢秀山, 王胜利, 等. 一种基于改进自适应卡尔曼滤波的GNSS/INS组合导航算法[J]. 科学技术与工程, 2020, 20(3): 913-917. DOI: 10.3969/j.issn.1671-1815.2020.03.007
    [19] JIANG H T, LI T, SONG D, et al. An effective integrity monitoring scheme for GNSS/INS/vision integration based on error state EKF model[J]. IEEE sensors journal, 2022, 22(7): 7063-7073. DOI: 10.1109/JSEN.2022.3154054
    [20] LI S, MIKHAYLOV M, PANY T, et al. Exploring the potential of deep learning aided Kalman filter for GNSS/INS integration: a study on 2D simulation datasets[J]. IEEE transactions on aerospace and electronic systems, 2023: 1-10. DOI: 10.1109/TAES.2023.3325791
    [21] WU F, LUO H Y, JIA H W, et al. Predicting the noise covariance with a multitask learning model for Kalman filter-based GNSS/INS integrated navigation[J]. IEEE transactions on instrumentation and measurement, 2020(70): 1-13. DOI: 10.1109/TIM.2020.3024357
    [22] UENEY M, CLARK D E, JULIER S J. Distributed fusion of PHD filters via exponential mixture densities[J]. IEEE journal of selected topics in signal processing, 2013, 7(3): 521-531. DOI: 10.1109/JSTSP.2013.2257162
    [23] YIN Z H, YANG J H, MA Y, et al. A robust adaptive extended Kalman filter based on an improved measurement noise covariance matrix for the monitoring and isolation of abnormal disturbances in GNSS/INS vehicle navigation[J]. Remote sensing, 2023, 15(17): 4125. DOI: 10.3390/rs15174125
    [24] MOUSSA M, MOUSSA A, ELHABIBY M, et al. Wheel-based aiding of low-cost imu for land vehicle navigation in GNSS challenging environment[C]//IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), 2020: 1-6.
    [25] CHEN Q J, ZHANG Q, NIU X J. Estimate the pitch and heading mounting angles of the IMU for land vehicular GNSS/INS integrated system[J]. IEEE transactions on intelligent transportation systems, 2021, 22(10): 6503-6515. DOI: 10.1109/TITS.2020.2993052
    [26] ZHAO Y W. Cubature+extended hybrid Kalman filtering method and its application in PPP/IMU tightly coupled navigation systems[J]. IEEE sensors journal, 2015, 15(12): 6973-6985. DOI: 10.1109/JSEN.2015.2469105
    [27] 谢钢. GPS原理与接收机设计[M]. 北京: 电子工业出版社, 2017.
  • 加载中
图(12) / 表(2)
计量
  • 文章访问数:  126
  • HTML全文浏览量:  47
  • PDF下载量:  15
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-01-30
  • 网络出版日期:  2024-07-08

目录

    /

    返回文章
    返回