基于因子图结合卡方检测的多AUV协同定位方法  

Multi-AUV Cooperative Localization Method Based on Factor Graph Combined with Chi-Square Detection

作　　者：涂豫[1] 李国胜 覃羡烘 TU Yu;LI Guosheng;QIN Xianhong(Henan Polytechnic Institute,Nanyang 473000,China;School of Computer Science&Technology,Huazhong University of Science and Technology,Wuhan 430074,China;School of Information Engineering,Zhengzhou University,Zhengzhou 450001,China)

机构地区：[1]河南工业职业技术学院,南阳473000 [2]华中科技大学计算机科学与技术学院,武汉430074 [3]郑州大学信息工程学院,郑州450001

出　　处：《数据采集与处理》2021年第5期978-985,共8页Journal of Data Acquisition and Processing

摘　　要：针对复杂的水下环境导致水声通信噪声出现异常值的问题,提出一种基于因子图结合卡方检测的多AUV协同定位算法。建立因子图模型将全局函数估计问题转化为局部函数和积估计问题,利用卡方检测测距噪声异常值。所提算法在测距噪声存在异常值情况下,与传统Kalman滤波算法相比定位误差大幅减小。该研究进行了数学仿真验证,验证了所提算法可以有效提高系统的定位稳定性,处理测距噪声异常值对定位性能的影响。In order to solve the problem of abnormal value of underwater acoustic communication noise caused by complex underwater environment,a multi-AUV cooperative localization algorithm based on factor graph and chi-square detection is proposed.A factor graph model is developed to transform the global function estimation problem into a local function and product estimation problem,using cardinality to detect ranging noise outliers.The proposed algorithm significantly reduces the localization error compared with the conventional Kalman filtering algorithm in the presence of ranging noise outliers.The study is validated with mathematical simulations,showing that the proposed algorithm can effectively improve the positioning stability of the system and deal with the effects of ranging noise outliers on the positioning performance.

关 键 词：自主水下航行器 协同定位 因子图 噪声异常 卡方检测 

分 类 号：TN911.2[电子电信—通信与信息系统] TP24[电子电信—信息与通信工程]