【作者】 陈锋； 林志鹏； 刘玉超； 朱秋明； 周芳； 仲伟志； 叶前程；

【Author】 CHEN Feng;LIN Zhipeng;LIU Yuchao;ZHU Qiuming;ZHOU Fang;ZHONG Weizhi;YE Qiancheng;Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space,Nanjing University of Aeronautics and Astronautics;China Research Institute of Radiowave Propagation;

【机构】 南京航空航天大学电磁频谱空间认知动态系统重点实验室； 中国电波传播研究所；

【摘要】 本文提出了一种基于改进遗传算法的多目标协同定位方法,可以在复杂场景中实现多目标的识别与定位。该方法利用多个基站获取待测目标信号传播时间信息,基于到达时间估计待测多目标的位置信息。在考虑定位时间约束下,通过引入模拟退火算法Metroplies准则,所提方法利用遗传算法对定位基站进行选择,并经过迭代择优提高对目标的定位精度。仿真结果表明,本文提出的方法可以实现多目标节点的识别以及定位,定位精度相较于传统到达时间法有40%～60%的提升。更多还原

【Abstract】 Based on an improved genetic algorithm,this paper presents a multi-target collaborative positioning method,which can achieve multi-target identification and positioning in complex scenarios.By using signal propagation time information of targets from multiple base stations,the method estimate the target locations based on time of arrival(TOA).Considering the positioning time constraints,the proposed method uses genetic algorithm to select the positioning base stations by introducing Metroplies criterion of the simulated annealing algorithm,and improves the positioning accuracy of the targets through iterative selection.Simulation results show that the proposed method can identify and locate multiple targets.Compared with the traditional TOA positioning methods,the positioning accuracy of our method can improve 40%-60%.更多还原