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The fault detection and fault tolerance technology of autonomous underwater vehicle(AUV)navigation system is an important guarantee for the implementation of modern marine strategy. It summarizes the research progress of fault diagnosis methods of AUV integrated navigation and cooperative navigation system at home and abroad in recent years, including the fault detection methods based on analytical model,sensor signal processing, artificial intelligence and short-time sensor failure tolerance technology. And the application conditions, advantages and disadvantages of various algorithms are analyzed. Aiming at the fault tolerance methods of multi-sensor information fusion in the underwater navigation system, the advantages,disadvantages and technical difficulties of existing multi-sensor fault tolerance algorithms are compared and summarized. Meanwhile, the future development trend of fault detection and information fusion fault tolerance algorithm in underwater integrated navigation and cooperative navigation system is prospected, which gives a reference for the fault diagnosis and fault tolerance direction of AUV navigation system.
[1] Chai F,Johnson K S,Claustre H,et al,Monitoring ocean bio-geochemistry with autonomous platforms[J].Nature Reviews Earth&Environment,2020,1:315-326.
[2]杨锐，马英杰，程世婧.海洋观测探测平台关键材料发展与展望[J].中国科学院院刊，2022,37(7):881-887.
[3]张佳欣，张森林，刘妹琴，等.面向海洋环境自适应采样的多AUV协同定位[J].智能科学与技术学报，2022,4(4):503-512.
[4]吴有生，司马灿，朱忠，等.海洋装备技术的重点发展方向[J].前瞻科技，2022,1(2):20-35.
[5] Tan Y W,Wang J D,Liu J J,et al. Unmanned systems security:Models,challenges and future directions[J]. IEEE Network,2020,34(4):291-297.
[6] Pauli L,Saeedi S,Seto M,et al. AUV navigation and localization:A review[J]. IEEE Journal of Oceanic Engineering,2014,39(1):131-149.
[7]白瑜亮，史晓宁，王思.自主水下航行器非线性鲁棒动态逆姿态控制系统设计[J].战术导弹技术，2016(4):93-97.
[8]黄玉龙，张勇刚，赵玉新.自主水下航行器导航方法综述[J].水下无人系统学报，2019,27(3):232-253.
[9]徐博，白金磊，郝燕玲，等.多AUV协同导航问题的研究现状与进展[J].自动化学报，2015,41(3):445-461.
[10]朱兵，常国宾，何泓洋，等. SINS/DVL/AST水下组合导航中的鲁棒信息融合方法[J].国防科技大学学报，2020,42(5):107-114.
[11]于玖成，何昆鹏，王晓雪. SINS/DVL组合导航系统的标定[J].智能系统学报，2015,10(1):143-148.
[12]李旻.基于SINS/DVL与声学定位系统的水下组合导航技术研究[J].舰船电子工程，2018,38(12):60-64.
[13]李怀建，徐荣景，杜小菁，等.组合导航系统故障检测算法研究现状分析[J].战术导弹技术，2021,(1):99-106.
[14]郭鑫，刘小雄，何启志，等.基于UKF的水下航行器IMU故障检测与诊断方法研究[J].计算机测量与控制，2019,27(8):30-34+39.
[15] Iqbal R, Maniak T, Doctor F, et al. Fault detection and isolation in industrial processes using deep learning approaches[J]. IEEE Transactions on Industrial Informatics,2019,15(5):3077-3084.
[16]史雨茹.基于集员估计方法的主动故障检测[D].北京化工大学，2020.
[17] Bhatt D,Aggarwal P,Devabhaktuni V,et al. A novel hybrid fusion algorithm to bridge the period of GPS outages using low-cost INS[J]. Expert Systems with Applications,2014,41(5):2166-2173.
[18]李永强，唐旭东，李兆凯，等.移动机器人的多传感器信息融合[J].西北工业大学学报，2021, 39(S1):59-65.
[19]赵炳巍，曹岩，贾峰，等.移动机器人多传感器信息融合方法综述[J].电子测试，2020(18):68-69.
[20] Brumback B D, Srinath M D. A chi-square test for fault-detection in Kalman Filters[J]. IEEE Transactions on Automatic Control,1987,AC-32(6):552-554.
[21]张华强，李东兴，张国强.混合χ~2检测法在组合导航系统故障检测中的应用[J].中国惯性技术学报，2016,24(5):696-700.
[22]姜颖颖，潘树国，叶飞，等.基于抗差估计和改进AIME的缓变故障检测方法[J].系统工程与电子技术，2022,44(9):2894-2902.
[23]潘绍华，徐晓苏，张亮.基于卡方检测和相关向量机的DVL异常信息处理机制[J].中国惯性技术学报，2022,30(4):461-468.
[24] Guerra P, Puig V, Ingimundarson A, et al. Robust fault detection with unknown input set-membership state estimators and interval models using Zonotopes[C]. Proceedings of the 6th Fault Detection, Supervision and Safety of Technical Processes 2006, Beijing, China:Elsevier Science Ltd,2006:1234-1239.
[25] Tang W, Wang Z, Shen Y, et al. Fault detection based on multi-objective observer and interval Hull computation[C]. Proceedings of the 10th IFAC Symposium on Fault Detection,Supervision and Safety for Technical Processes SAFEPROCESS 2018, Warsaw, Poland:Elsevier Science Ltd,2018:332-337.
[26]韩斌子，胡柏青.基于时间序列建模的组合导航系统故障诊断[J].哈尔滨工程大学学报，2018, 39(11):1843-1847.
[27] Donoho D L,Johnstone I M. Ideal spatial adaptation by wavelet shrinkage[J]. Biometrika,1994,81(3).
[28] Abubakar U,Mekhilef S,Gaeid K S,et al. Induction motor fault detection based on multi-sensory control and wavelet analysis[J]. IET Electric Power Applications,2020,14(11):2051-2061.
[29] Yan R,Gao R X,Chen X. Wavelets for fault diagnosis of rotary machines:A review with applications[J]. Signal Processing,2014,96:1-15.
[30]焦新涛.小波分析及其在齿轮箱故障诊断中应用研究[D].广州：华南理工大学，2014.
[31]张铭钧，殷宝吉，刘维新，等.随机干扰下AUV推进器故障特征提取与融合[J].华中科技大学学报（自然科学版），2015,43(6):22-26+54.
[32] Jiang Y,He B,Lv P,et al. Actuator fault diagnosis in autonomous underwater vehicle based on principal component analysis[C]. Kaohsiung:IEEE Underwater Technology,2019.
[33]吴磊，姜南，奔粤阳，等.结合主元分析与组合导航的容错算法[J].电光与控制，2020,27(7):95-100.
[34]许飞.基于集合经验模态分解方法的GNSS监测数据处理[J].测绘技术装备，2022,24(3):102-109.
[35]甄岩，袁健全，池庆玺，等.深度强化学习方法在飞行器控制中的应用研究[J].战术导弹技术，2020(4):112-118.
[36]姜晓伟，王春平，付强.卷积神经网络及其在目标检测中的应用[J].战术导弹技术，2019(1):108-114+123.
[37]刘东涛.基于改进决策树的导航系统故障诊断的研究[J].现代导航，2022,13(5):334-338.
[38]付中泽，陈伟，韩金良.人工智能在舰船组合导航系统的应用[J].舰船科学技术，2020,42(19):152-156.
[39] Xu H,Lian B. Fault detection for multi-source integrated navigation system using fully convolutional neural network[J]. Sonar&Navigation,2018,12(7):774-782.
[40] Mokhtari S, Abbaspour A, Kang K Y, et al. Neural network-based active fault-tolerant control design for unmanned helicopter with additive faults[J]. Multidisciplinary Digital Publishing Institute, 2021, 13(12),2396.
[41]赵修斌，高超，庞春雷，等. BP神经网络辅助的缓变故障双阈值检测法[J].控制与决策，2020,35(6):1384-1390.
[42] Ma H. Mu X. He B. Adaptive navigation algorithm with deep learning for autonomous underwater vehicle[J].Sensors 2021,21,6406.
[43]魏奥博，郑荣. SVR辅助SINS-DVL的水下机器人组合导航方法[J].舰船科学技术，2020,42(01):161-167.
[44] Li D,Xu J,He H,et al. An underwater integrated navigation algorithm to deal with DVL malfunctions based on deep learning[J]. IEEE Access,2021,PP(99):1-1.
[45] Zhao L Y, Liu X J, Wang L, et al. A pretreatment method for the velocity of DVL based on the motion constraint for the integrated SINS/DVL[J]. Applied Sciences,2016,6(3):1-15.
[46] Huang Y L, Zhang Y G, Wu Z M, et, al. A novel adaptive Kalman filter with inaccurate process and measurement noise covariance matrices[J]. IEEE Transactions on Automatic Control,2018,63(2):594-601.
[47] Kim J. Cooperative localization and unknown currents estimation using multiple autonomous underwater vehicles[J]. IEEE Robotics and Automation Letters, 2020, 5(2):2365-2371.
[48]张立川，许少峰，刘明雍，等.多无人水下航行器协同导航定位研究进展[J].高技术通讯，2016,26(5):475-482.
[49]孙成娇.基于声学测距的水下协同导航状态估计方法研究[D].哈尔滨：哈尔滨工程大学，2019.
[50]徐博，王权达，李盛新，等.基于马氏距离结合自适应滤波的协同定位方法[J].中国惯性技术学报，2021,29(5):617-624.
[51]徐博，李盛新，王连钊，等.基于ANFIS的多AUV协同定位系统量测异常检测方法[J/OL].自动化学报：1-13. DOI:10. 16383/j. aas. c20092 1. 1.
[52]李万里，陈明剑，张伦东，等.基于新息的SINS/DVL组合导航自适应滤波算法[J].兵器装备工程学报，2020,41(12):225-229+252.
[53]刘菲，王志，戴晔莹，等.基于预测残差的抗差自适应滤波组合导航算法[J].北京航空航天大学学报，2023,49(06):1301-1310.
[54] Carlson N A. Federated filter for fault-tolerant integrated navigation systems[C]. IEEE PLANS'88. Position Location and Navigation Symposium,Record'Navigation into the 21st Century. Orlando,FL,USA,1988,pp. 110-119.
[55]耿峰，祝小平，周洲.一种有效的组合导航容错滤波技术研究[J].西北工业大学学报，2016,34(3):449-455.
[56]马晓爽，刘锡祥，张同伟，等.基于因子图的AUV多传感器组合导航算法[J].中国惯性技术学报，2019,27(4):454-459.
[57]黄紫如，柴洪洲，向民志，等.考虑信息滞后的AUV因子图多源信息融合定位算法[J].中国惯性技术学报，2021,29(5):625-631.
[58]孙克诚，曾庆化，王守一，等.基于因子图导航的伪距故障检测与自适应隔离方法[J].中国惯性技术学报，2022,30(1):65-73.
Basic Information:
DOI：10.16358/j.issn.1009-1300.20230045
China Classification Code:U666.1
Citation Information:
[1]Wang Quanda,Xu Bo,Zhang Tao.Review on fault diagnosis and fault tolerance technology of AUV navigation system[J].Tactical Missile Technology,2023,No.220(04):26-36+5.DOI:10.16358/j.issn.1009-1300.20230045.
Fund Information:
黑龙江省自然科学基金（LH2022F014）
2023-07-19
2023-07-19
2023-07-19