Analysis and implementation of multi-cooperative target location algorithm based on distance measurement

Shixiong Luo, Chuangang Xu, Jiangpeng Song
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Abstract

Aiming at the problem of reconnaissance and positioning of ground targets by airborne photoelectric detection equipment, this paper firstly studies the problem and model of multi-cooperative positioning based on distance measurement, and analyzes the factors affecting the positioning accuracy. Then, three solving methods of multicooperative target location based on distance measurement are proposed: least square algorithm, traditional particle swarm optimization algorithm and improved particle swarm optimization algorithm based on least square. The positioning accuracy and efficiency of the above three algorithms are simulated and compared in MATLAB, and the above algorithms are verified by flight test data. The experimental results show that the improved particle swarm optimization algorithm based on least squares has high computational accuracy and efficiency for solving the location equation of cooperative distance measurement.
基于距离测量的多合作目标定位算法的分析与实现
针对机载光电探测设备对地面目标的侦察定位问题,本文首先研究了基于距离测量的多目标协同定位问题和模型,分析了影响定位精度的因素。然后,提出了基于距离测量的多目标协同定位的三种求解方法:最小平方算法、传统粒子群优化算法和基于最小平方的改进粒子群优化算法。在 MATLAB 中对上述三种算法的定位精度和效率进行了仿真和比较,并通过飞行测试数据对上述算法进行了验证。实验结果表明,基于最小二乘法的改进粒子群优化算法在求解协同测距的定位方程时具有较高的计算精度和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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