存在障碍物影响的多AUV间距离量测识别与平滑算法  

Range Measurement Smoothing Algorithm for Multiple AUV under the Influence of Obstacles

作　　者：马朋[1] 张福斌[1] 刘书强[1] 徐德民[1] Ma Peng Zhang Fubin Liu Shuqiang Xu Demin(School of Marine Science and Technology, Northwestern Polytechnical University, Xi＇an 710072, China)

机构地区：[1]西北工业大学航海学院,陕西西安710072

出　　处：《西北工业大学学报》2017年第4期643-647,共5页Journal of Northwestern Polytechnical University

基　　金：国家自然科学基金(61273333)资助

摘　　要：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。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 obsta- cle-related NLOS （ONLOS） measurements is proposed. On the basis of classification results, we construct the dy- namic model of range measurements between AUV, and design a smoothing sing the Kalman filter method. Simulation results indicate that the proposed algorithm for range measurements by u- algorithm improves the estimation accu- racy of relative range measurements between leader and follower AUV, and mitigates the influence of ONLOS meas- urements errors to the performance of multiple AUV cooperative localization.

关 键 词：多自主水下航行器 水下障碍物 非视距量测 朗伯w函数 量测识别 距离平滑 协同定位 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]