A Parallel Integration Method of Cooperative Target-Localization and Cooperative Self-localization  

一种协作目标定位与协作自定位的并行集成方法

作　　者：WANG Leigang KONG Depei ZHOU Jihang WANG Jianlu 王雷钢;孔德培;周继航;王建路(电子信息系统复杂电磁环境效应国家重点实验室,洛阳471003)

机构地区：[1]State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System,Luoyang 471003,P.R.China

出　　处：《Transactions of Nanjing University of Aeronautics and Astronautics》2022年第2期231-238,共8页南京航空航天大学学报（英文版）

摘　　要：When a group of mobile agents track a target,they can locate themselves and the target in a cooperative manner.To maximize the group advantage,a parallel integration strategy of cooperative target-localization(CTL)and cooperative self-localization(CSL)is designed.Firstly,a global cost function containing the agents’positions and the target’s position is established.Secondly,along with the agents’positions being re-estimated during CTL,the Utransform is employed to propagate the error covariance of the position estimations among the agents.The simulation results show that,the proposal exploits more information for locating the target and the agents than the cases where CTL and CSL run separately,and the global optimal position estimations of the agents and the target are obtained.当群智能体在进行目标跟踪时,它们可以以协作的方式对自身和目标进行定位。为了最大限度地发挥群协作的优势,本文设计了一种协作目标定位(Cooperative target-localization,CTL)和协作自定位(Cooperative target-localization,CSL)的并行集成的运行策略。首先,建立一个包含群智能体位置和目标位置的全局代价函数。其次,在CTL过程中,随着智能体位置被重新估计,使用U变换推算各智能体位置估计之间的误差协方差。仿真结果表明,与CTL和CSL独立运行的情况相比,该策略利用了更多的信息进行目标和智能体的位置估计,可以获得全局最优的智能体和目标位置估计结果。

关 键 词：cooperative self-localization cooperative target-localization non-classical multi-dimensional scaling majoring function 

分 类 号：TN925[电子电信—通信与信息系统]