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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。
Non-line-of-sight (NLOS) errors have a significant impact on the positioning accuracy of UWB indoor positioning technology. To solve this problem, the mean and variance of NLOS errors are estimated according to the statistical properties of the additional delay in NLOS environment and the root mean square delay spread determined by the channel, and the covariance of the measured location and system measurement error is corrected The time-varying weighted particle swarm optimization algorithm is combined with the Chan algorithm to locate and calculate the co-location algorithm, which has the good ability of global search and local search optimal solution. Simulation results show that compared with a single algorithm, the positioning accuracy of the cooperative algorithm is improved by about 30% in NLOS environment, to a certain extent, the influence of NLOS error is suppressed, and the requirement of indoor positioning is satisfied.