基于主从式水下自主航行器移动组网的合作目标定位方法

利用水下自主航行器(AUVs)协同编队可以在未知水域中实现对目标的定位。针对AUV导航误差导致定位精度降低问题，该文提出一种基于扩展卡尔曼滤波器(EKF)的多AUV编队融合观测协同目标定位算法。AUV编队由一个装备有高精度惯性导航系统(INS)的领航AUV以及多个装配有低精度INS的跟随AUV组成。从跟随AUV中选取参考AUV和待测AUV，通过设置定位周期和观测间隔来分别对其进行不同的观测。参考AUV作为中转，接收来自高精度AUV位置参数后，向待测AUV传递自身位置参数，利用扩展卡尔曼滤波器完成对AUV集群的协同位置修正。仿真结果表明，该方法AUV集群自身定位精度高且误差随时间积累小，对领航AUV数量需求少，能够实现水下目标低功耗、远距离定位。

Cooperative Target Location Method Based on Master-slave Autonomous Underwater Vehicles Mobile Network

The cooperative formation of Autonomous Underwater Vehicles (AUVs) can be used to locate targets in unknown waters. In order to reduce the positioning error caused by AUV navigation errors, a multi-AUV formation fusion observation cooperative target positioning algorithm based on Extended Kalman Filter (EKF) is proposed in this paper. The AUV formation consists of a pilot AUV equipped with a high precision Inertial Navigation System (INS) and several following AUVs equipped with low precision INS. The reference AUV and the AUV to be measured are selected from the following AUV, and different observations are made respectively by setting the positioning period and observation interval. After receiving position parameters from high-precision AUV with reference to AUV as relay, its own position parameters are transmitted to the AUV to be tested, and cooperative position correction of AUV cluster is completed with extended Kalman filter. Simulation results show that the AUV cluster has high positioning accuracy and small error accumulation over time, which requires less piloting AUV quantity and can achieve low power consumption and long-distance positioning of underwater targets.