摘要 由于室内多径信号丰富且包含了室内几何信息，可以利用室内多径信号对目标进行定位.基于此，本文提出了一种多径辅助的目标定位算法.首先，利用多径信号的差分飞行时间（Time of Flight，TOF）构建关于目标以及散射体位置的适应度函数；然后，提出了基于粒子群优化（Particle Swarm Optimization，PSO）的目标及散射体位置联合搜索算法，其中利用目标及散射体到达角（Angle of Arrival，AOA）确定搜索范围；其次，选取搜索到的散射体位置联合差分TOF求解目标位置；最后，利用仿射传播聚类（Affinity Propagation Clustering，APC）对所有散射体估计到的目标位置进行聚类，提出聚类准则消除大的定位误差点.仿真结果表明，本文所提算法利用单个基站可以达到较高定位精度.
Abstract：Multipath signals can be used to realize localization since they are abundant and contain geometry information of indoor environments.Based on this,this paper proposes a multipath-assisted target localization algorithm.Firstly,the fitness function about the target and scatterer locations is constructed with Time of Flight (TOF) differences.Then,the locations of the target and scatterers are searched jointly by Particle Swarm Optimization (PSO) and Angle of Arrivals (AOAs) that determines searching ranges.Secondly,the estimated locations of scatterers and TOF differences are used to estimate the target location.Finally,all target locations are clustered by using Affinity Propagation Clustering (APC),and a clustering criterion is proposed to eliminate big localization errors.The simulation results show that the proposed algorithm can achieve high localization accuracy with a single base station.
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2020, Vol. 48 
