NLOS环境下基于自适应遗传算法的TOA/AOA定位算法

在视距传播(LOS)环境下,波达时间/电波到达角(TOA/AOA)定位算法比TOA算法的定位精度有了进一步的提高,但是在非视距传播(NLOS)环境下,这些定位算法的精度会受到较大影响。为了减小NLOS传播的影响,提出了一种NLOS环境下的TOA/AOA定位算法。利用自适应遗传算法对TOA/AOA混合定位算法中的非线性优化问题进行求解,从而提高系统的定位精度。仿真结果表明,提出的算法在NLOS环境下有较高的定位精度,性能优于Chan算法和LS算法。

A TOA/AOA location algorithm based on adaptive genetic algorithm in NLOS environment

In Line - Of - Sight（LOS）environment, TOA/AOA location algorithm has better accuracy than TOA location algorithm, but in Non- Line- Of- Sight（NLOS）environment, location accuracy of these algorithms will be affected greatly. In order to mitigate the effect of NLOS propagation, an adaptive genetic algorithm is proposed for the nonlinear optimization in TOA/AOA location algorithm, and to improve the location accuracy. The simulation results indicate that the location accuracy is significantly improved and the performance of this algorithm is better than that of Chan algorithm and LS algorithm in NLOS environment.