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Mixed near-field and far-field source localization revised: propagation loss included
Multidimensional Systems and Signal Processing ( IF 1.7 ) Pub Date : 2019-10-08 , DOI: 10.1007/s11045-019-00683-2
Pourya Behmandpoor , Farzan Haddadi

This paper is concerned with source localization when path loss is taken into account. We modify multiple signal classification method to localize near-field sources whose received power is different in the sensors of the array due to path loss. Traditional methods fail to localize the sources, and they also fail to separate the bearing estimation and the range estimation of the sources, when path loss is considered. We suggest a T-shaped array avoiding multidimensional search to estimate source location parameters, separately. At the first step, the ranges of the signal sources are estimated, and then at the second step, the directions of arrival of the sources are estimated using the respective ranges determined at the first stage. The performance of the proposed method is assessed when mixed near-field and far-field sources coexist. Simulation results are presented to show the superior performance of the proposed algorithm compared to the existing techniques and the Cramer–Rao bound.

中文翻译:

混合近场和远场源定位修订:包括传播损耗

本文关注的是考虑路径损耗时的源定位。我们修改了多信号分类方法,以定位由于路径损耗而在阵列传感器中接收功率不同的近场源。在考虑路径损耗时,传统方法无法定位源,并且它们也无法将源的方位估计和距离估计分开。我们建议使用 T 形阵列避免多维搜索来分别估计源位置参数。在第一步,估计信号源的距离,然后在第二步,使用在第一阶段确定的各个距离估计信号源的到达方向。当混合近场和远场源共存时,评估所提出方法的性能。
更新日期:2019-10-08
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