Abstract: In order to mitigate the effect of NLOS propagation, a TDOA/AOA localization algorithm based on the RBF neural network is proposed. The RBF neural network is made use of to correct the error of NLOS propagation, then position is calculated by TDOA/AOA algorithm. The simulation results indicate that the effect of NLOS propagation is mitigated by this algorithm. Its location accuracy is significantly improved and the performance of this algorithm is better than that of TDOA/AOA algorithm, Taylor algorithm, Chan algorithm and LS algorithm in NLOS environment.

Key words: TDOA, AOA, NLOS, neural network

摘要： 为了减小NLOS传播的影响，提出基于RBF网络的TDOA/AOA算法。利用RBF神经网络对NLOS传播的误差进行修正，使用TDOA/AOA算法进行定位。仿真结果表明该算法减小了NLOS传播的影响，在NLOS环境下有较高的定位精度，性能优于TDOA/AOA算法、Taylor算法、Chan算法和最小二乘(LS)算法。

关键词: 到达时间差, 到达角, 非视距传播, 神经网络

CLC Number: 

• TN929.53