Directions of Arrival estimation of correlated sources in presence of Mutual coupling

S. Akkar, F. Harabi, A. Gharsallah
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Abstract

This paper proposes a self-calibration algorithm, that requires only real valued operations, to estimate the Directions of Arrival (DoAs) of correlated sources in the presence of unknown Mutual coupling. Based on the standard MUSIC algorithm and with respect to the same imposed constraints, we develop the Iterative Unitary-MUSIC algorithm that provides superior high resolution localisation capabilities even for correlated sources scenarios with a reduced computations cost as well as a low processing time compared with previous works. In our analysis, the induced Electro-Motive Force (EMF) method is used to model the mutual coupling matrix. Through computer simulations, we demonstrate that our approach has more interesting performances even if all coupling parameters are included and especially when the incoming signals are highly correlated. Moreover, we drive more flexible identifiability conditions for the uniqueness of the estimation solution that required a reduced number of sensors to estimate the same number of parameters compared with previous works.
相互耦合下相关源的到达方向估计
本文提出了一种自校正算法,该算法只需要实值运算即可估计未知互耦情况下相关源的到达方向(DoAs)。基于标准MUSIC算法并考虑到相同的强加约束,我们开发了迭代一元MUSIC算法,该算法提供了优越的高分辨率定位能力,即使对于相关源场景,与以前的工作相比,计算成本降低,处理时间也缩短。在我们的分析中,采用感应电动势(EMF)方法来模拟互耦矩阵。通过计算机模拟,我们证明了即使包括所有耦合参数,特别是当输入信号高度相关时,我们的方法也有更有趣的性能。此外,我们为估计解决方案的唯一性驱动了更灵活的可识别条件,与以前的工作相比,需要减少数量的传感器来估计相同数量的参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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