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A Weighting Localization Algorithm with LOS and One-Bound NLOS Identification in Multipath Environments

机译:多路径环境下具有LOS和单界NLOS识别的加权定位算法

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摘要

Mobile station (MS) localization often suffers from hybrid line of sight (LOS), one-bound (OB) and multiple-bound (MB) non-line of sight (NLOS) propagation in multipath environments. Due to the unknown propagation path, accurate position estimate of MS is challenging through using the measured angle of departure (AOD), angle of arrival (AOA), and time of arrival (TOA) of signal between MS and base station (BS). To address this problem, a new weighting localization algorithm based on LOS and OB NLOS identification is proposed in this paper. For each propagation path, by utilizing the geometric relation between AOD and AOA, a theoretic threshold is derived to decide whether it is LOS or NLOS propagation. Moreover, in order to further discriminate OB or MB NLOS propagation, an effective cost function is formulated and an iterative OB NLOS identification method is proposed to discard MB NLOS propagation paths. Finally, a weighting localization algorithm is applied for fusing the measured data of LOS and OB NLOS propagation paths. Simulation results demonstrate that simulation of LOS identification method is consistent with theoretic one, and the proposed algorithm can greatly improve the localization accuracy of MS in different multipath environments, especially when LOS path is available.
机译:在多径环境中,移动站(MS)的定位经常遭受混合视线(LOS),单界(OB)和多界(MB)​​非视线(NLOS)传播的困扰。由于未知的传播路径,通过使用测得的MS与基站(BS)之间信号的离开角(AOD),到达角(AOA)和到达时间(TOA),对MS进行准确的位置估计非常具有挑战性。针对这一问题,本文提出了一种新的基于LOS和OB NLOS识别的加权定位算法。对于每个传播路径,通过利用AOD和AOA之间的几何关系,导出理论阈值来确定它是LOS传播还是NLOS传播。此外,为了进一步区分OB或MB NLOS的传播,提出了一种有效的代价函数,并提出了一种迭代的OB NLOS识别方法,以丢弃MB NLOS的传播路径。最后,采用加权定位算法融合LOS和OB NLOS传播路径的测量数据。仿真结果表明,LOS识别方法的仿真与理论相吻合,所提出的算法可以大大提高MS在不同多径环境下的定位精度,特别是在LOS路径可用的情况下。

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