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 algorithm for range measurements by u?sing the Kalman filter method. Simulation results indicate that the proposed 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.%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.
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