针对舰船导航系统多源信息融合中故障检测问题，提出一种改进的残差${{\chi }^2}$检测算法。该算法克服了传统残差${{\chi}^2}$检测算法对门限设置敏感的缺点，通过适当的递推与合理的状态切换，使得改进${{\chi }^2}$检测算法受设置门限的影响大大降低，采用一定范围内的门限可达到相同效果，即可采用较宽泛的门限，有利于工程应用设计。仿真结果表明，改进算法相比传统算法能够在精度、稳定度和最大误差值3个方面获得较大改善，将位置误差降低到传统算法位置误差的18%，位置误差波动性降低至传统算法的14%，最大位置误差降低至传统算法的13%。
Aiming at the problem of fault detection in multi-source information fusion of navigation system, an improved detection algorithm base on residual chi-square is proposed. The proposed algorithm overcomes the disadvantage of the traditional residual detection algorithm base on residual chi-square that is sensitive to threshold setting. Through appropriate recursion and reasonable state switching. The influence of threshold setting on the improved detection algorithm is greatly reduced. Using a certain range of threshold can achieve the same effect, that is, a wider threshold can be used, which is very conducive to engineering application design. The simulation results show that the improved algorithm can greatly improve the accuracy, stability and maximum error compared with the traditional algorithm. The position error is reduced to 18% of the position error of the traditional algorithm, the fluctuation of position error is reduced to 14% of the traditional algorithm, and the maximum position error is reduced to 13% of the traditional algorithm.
2022,44(13): 144-148 收稿日期：2021-10-09
DOI：10.3404/j.issn.1672-7649.2022.13.031
分类号：TN965
基金项目：中国船舶集团预研项目（KJW202016）
作者简介：徐峰(1980-),男,高级工程师,主要从事舰船作战系统研究工作
参考文献：
[1] 赵万龙, 孟维晓, 韩帅. 多源融合导航技术综述[J]. 遥测遥控, 2016(6): 54–60
[2] 张靖, 陈鸿跃, 陈雨, 等. 一种基于联邦卡尔曼滤波器的多源信息融合定位算法[J]. 导弹与航天运载技术, 2018(2): 90–98
[3] WANG R, XIONG Z, LIU J, et al. Chi-square and SPRT combined fault detection for multisensor navigation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52(3): 1352–1365
[4] XU J, XIONG Z, LIU J, et al. A dynamic vector-formed information sharing algorithm based on two-state chi square detection in an adaptive federated filter[J]. The Journal of Navigation, 2019, 72(1): 101–120
[5] 杨镜, 华冰, 熊智. 多源导航系统软、硬故障检测新方法研究[J]. 压电与声光, 2013, 35(5): 647–652
[6] 张闯, 赵修斌, 庞春雷, 等. LS-SVM 辅助的小幅值及缓变故障检测与容错方法[J]. 中国惯性技术学报, 2019, 27(3): 415–420
[7] CHENG J, SUN X, LIU P, et a1. An improved residual Chi-square test fault isolation approach in four-gyro SINS[J]. IEEE Access, 2019, PP(99): l–1
[8] 郭慧娟, 刘慧英, 石静, 等. 基于自适应分类容错滤波的SINS/GNSS组合导航方法[J]. 中国惯性技术学报, 2018, 26(1): 39–44
[9] 李振威, 程咏梅, 刘刚, 等. INS/ADS/GPS组合导航高灵敏故障检测和识别方法[J]. 中国惯性技术学报, 2020, 28(5): 694–700
[10] 周朋进, 吕志伟, 丛佃伟, 等. 基于双状态χ2检测和快速强跟踪AUKF 的组合导航算法[J]. 中国惯性技术学报, 2019, 27(6): 771–777
