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

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.