一种基于非视距误差补偿的协同定位算法

非视距(NLOS)误差对超宽带(UWB)室内定位技术的定位精度有很大影响。针对此问题,根据NLOS环境下附加时延和由信道决定的均方根时延扩展的联合统计特性,估计NLOS误差的均值和方差,对定位算法测量值和系统测量误差协方差进行修正,并采用时变权重的粒子群算法与Chan算法相结合的协同定位算法进行定位计算,具有良好的全局搜索与局部搜索最优解的能力。仿真结果表明,在NLOS环境下,相比于单一算法,协同算法定位精度提高30%左右,在一定程度上抑制了NLOS误差的影响,满足室内定位的要求。

A collaborative localization algorithm based on non-line-of-sight error compensation

The non-line-of-sight (NLOS) error has great influence on the positioning accuracy of the ultra-wideband (UWB) indoor positioning technology.Aimed at this problem,this paper estimates the mean and variance of NLOS according to the joint statistical properties of the additional time delay in NLOS and the root mean square delay spread decided by the channel,modifies the measurements of the localization algorithm and the covariance of the systematic measurement error,and uses a collaborative localization algorithm,which combines the particle swarm optimization algorithm with time-varying weight and Chan algorithm and has a favorable ability of global search and local search for optimal solutions.The simulation result shows that the collaborative algorithm improves the positioning accuracy by about 30％,compared to a single algorithm.It,to a certain extent,inhibits the effect of NLOS error,and meets the requirements of indoor location.