%0 Journal Article
%T 存在障碍物影响的多AUV间距离量测识别与平滑算法<br>Range Measurement Smoothing Algorithm for Multiple AUV under the Influence of Obstacles
%A 马朋
%A 张福斌
%A 刘书强
%A 徐德民
%J 西北工业大学学报
%D 2017
%X 相互间距离量测信息是多AUV协同定位的基础。利用朗伯W函数求解AUV间的RSS距离估计，并通过TOA及RSS 2种距离量测结果的比较，引入一种障碍物引起的非视距（ONLOS）量测识别方法。在此识别基础上，建立了多AUV间距离量测动态变化模型，并利用Kalman滤波方法设计了ONLOS距离量测误差平滑算法。仿真结果表明，该算法可有效提高领航与跟随AUV间的相对距离量测估计精度，减轻ONLOS量测误差对多AUV协同定位性能的影响。<br>The range measurement information is the foundation of multiple AUV cooperative localization. In this paper, we use the Lambert W function to calculate the RSS range measurements between AUV. Then through the results of comparison between range measurements obtained with TOA and RSS, a classification algorithm for obstacle-related NLOS (ONLOS) measurements is proposed. On the basis of classification results, we construct the dynamic model of range measurements between AUV, and design a smoothing algorithm for range measurements by using the Kalman filter method. Simulation results indicate that the proposed algorithm improves the estimation accuracy of relative range measurements between leader and follower AUV, and mitigates the influence of ONLOS measurements errors to the performance of multiple AUV cooperative localization
%K 多自主水下航行器
%K 水下障碍物
%K 非视距量测
%K 朗伯W函数
%K 量测识别
%K 距离平滑
%K 协同定位&lt
%K br&gt
%K multiple autonomous underwater vehicles
%K underwater obstacles
%K non line of sight measurement
%K Lambert W function
%K measurement identification
%K range smoothing
%K cooperative localization
%U http://journals.nwpu.edu.cn/xbgydxxb/CN/abstract/abstract6812.shtml