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LCRT: A ToA Based Mobile Terminal Localization Algorithm in NLOS Environment

机译:LCRT:NLOs环境下基于Toa的移动终端定位算法

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摘要

Non line-of-sight (NLOS) propagation in range measurement is a key problem for mobile terminal localization. This paper proposes a low computational residual test (LCRT) algorithm that can identify the number of line-of-sight (LOS) transmissions and reduce the computational complexity compared with the residual test (RT) algorithm. LCRT is based on the assumption that when all range measurements are from LOS propagations, the normalized residual distribution follows the central chi-square distribution while for NLOS cases it is non-central. An optimized procedure to generate the sets of range measurements is adopted and least square (LS) instead of approximate maximum likelihood (AML) is used during the identification of LOS propagations, resulting in reduced computation complexity. Simulation results show that the LCRT can efficiently identify the set of LOS. The correct decision rate is higher than 92% and the variances of results are approaching to the Cramer-Rao lower bound (CRLB) when there are more than 3 LOS propagations.
机译:距离测量中的非视距(NLOS)传播是移动终端定位的关键问题。本文提出了一种低计算残差测试(LCRT)算法,与残差测试(RT)算法相比,该算法可以识别视距(LOS)传输次数并降低了计算复杂性。 LCRT基于以下假设:当所有距离测量值均来自LOS传播时,归一化残差分布遵循中心卡方分布,而对于NLOS情况,则为非中心。采用了生成距离测量集的优化程序,并在识别LOS传播期间使用了最小二乘(LS)而不是近似最大似然(AML),从而降低了计算复杂性。仿真结果表明,LCRT可以有效地识别出LOS。正确的决策率高于92%,并且当LOS传播超过3个时,结果的方差接近Cramer-Rao下界(CRLB)。

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