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A hybrid SS-TOA wireless geolocation based on path attenuation under imperfect path loss exponent

机译:不完善路径损耗指数下基于路径衰减的混合SS-TOA无线地理定位

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We consider the wireless geolocation using the time of arrival (ToA) of radio signals in a cellular setting. The main concern in this paper involves the effects of the error knowledge of the path loss exponent (PLE). We derive the asymptotic error performance of the maximum likelihood (ML) estimator under the imperfect PLE. We point out that a previous method provides inaccurate performance prediction and then present a new method based on the Taylor series expansion. Numerical examples illustrate that the Taylor analysis captures the bias and the error variance of the ML estimator under the imperfect PLE better than the conventional method. Simulation results also illustrate that in the threshold region, the ML estimator outperforms the MC estimator even in the presence of the PLE error. However, in the asymptotic region the MC estimator and the ML estimator with the perfect PLE outperform the ML estimator under the imperfect PLE.
机译:我们使用蜂窝环境中无线电信号的到达时间(ToA)考虑无线地理位置。本文主要关注的是路径损耗指数(PLE)的错误知识的影响。我们得出不完全PLE下最大似然(ML)估计量的渐近误差性能。我们指出,先前的方法提供了不准确的性能预测,然后提出了基于泰勒级数展开的新方法。数值算例表明,与常规方法相比,Taylor分析在不完全PLE情况下更能捕获ML估计量的偏差和误差方差。仿真结果还表明,在阈值区域中,即使存在PLE误差,ML估计器的性能也要优于MC估计器。但是,在渐近区域中,具有理想PLE的MC估计器和ML估计器在不完善的PLE情况下优于ML估计器。

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