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A Hybrid SS–ToA Wireless NLoS Geolocation Based on Path Attenuation: ToA Estimation and CRB for Mobile Position Estimation

机译:基于路径衰减的SS-ToA无线NLoS混合地理位置定位:ToA估计和CRB用于移动位置估计

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摘要

We propose a new hybrid wireless geolocation scheme that requires only one observation quantity, namely, the received signal. The attenuation model is explored herein to capture the propagation features from the received signal. Thus, it provides a more accurate approach for wireless geolocation. To investigate geolocation accuracy, we consider the time-of-arrival (ToA) estimation in the presence of path attenuation. The maximum-correlation (MC) estimator is revisited, and the exact maximum-likelihood (ML) estimator is derived to estimate the ToA. The error performance of the ToA estimates is derived using a Taylor expansion. It is shown that the ML estimate is unbiased and has a smaller error variance than the MC estimate. Numerical results illustrate that, for a low effective bandwidth, the ML estimator well outperforms the MC estimator. Afterward, we derive the CramÉr–Rao bound (CRB) for the mobile position estimation. The obtained result, which is applicable to any value of path loss exponents, gives a generalized form of the CRB for the ordinary geolocation approach. In seven hexagonal cells, numerical examples show that the accuracy of the mobile position estimation exploring the path loss is improved compared with that obtained by the usual geolocation.
机译:我们提出了一种新的混合无线地理定位方案,该方案仅需要一个观测量,即接收信号。本文探讨了衰减模型,以从接收信号中捕获传播特征。因此,它为无线地理定位提供了更准确的方法。为了调查地理位置的准确性,我们考虑存在路径衰减的到达时间(ToA)估计。再次讨论最大相关(MC)估计器,并推导确切的最大似然(ML)估计器以估计ToA。 ToA估计的错误性能是使用泰勒展开式得出的。结果表明,与MC估计相比,ML估计是无偏的并且误差变化较小。数值结果表明,对于低有效带宽,ML估计器的性能明显优于MC估计器。之后,我们得出用于移动位置估计的CramÉr-Rao界(CRB)。得到的结果适用于任何路径损耗指数值,给出了普通地理定位方法的CRB的一般形式。在七个六角形单元中,数值示例表明,与通过常规地理位置获得的移动位置估计精度相比,探索路径损耗的移动位置估计精度有所提高。

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