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DOA, power and polarization angle estimation using sparse signal reconstruction with a COLD array

机译:使用稀疏信号重建和COLD阵列进行DOA,功率和偏振角估计

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摘要

Existing polarized source localization methods mostly rely on subspace technique. In this paper, a very different framework, namely sparse signal reconstruction, is extended to estimate direction-of-arrival (DOA), power and polarization angle parameters using a cocentered orthogonal loop and dipole (COLD) array. The key points of the proposed algorithm can be summarized as three aspects: (i) this paper first constructs a special second-order statistics vector by using sum-average arithmetic, which is only the function of DOA and power parameters; (ii) then this paper constructs another three special second-order statistics vectors, which are only the function of polarization parameters; (iii) this paper exploits Zhang penalty to enforce sparsity, which lead to almost unbiased index and amplitude estimation. This paper also demonstrates how to distinguish two sources using their polarization characteristics. Simulation results validate the effectiveness and superiority of the proposed algorithm. (C) 2015 Elsevier GmbH. All rights reserved.
机译:现有的极化源定位方法主要依靠子空间技术。在本文中,扩展了一个非常不同的框架,即稀疏信号重构,以使用共心正交环路和偶极子(COLD)阵列来估计到达方向(DOA),功率和偏振角参数。该算法的关键点可以概括为三个方面:(i)本文首先利用求和平均算法构造了一个特殊的二阶统计向量,它仅是DOA和功率参数的函数; (ii)然后,本文构造另外三个特殊的二阶统计向量,它们仅是极化参数的函数; (iii)本文利用张罚分来执行稀疏性,从而导致几乎无偏的索引和幅度估计。本文还演示了如何利用它们的偏振特性来区分两个源。仿真结果验证了该算法的有效性和优越性。 (C)2015 Elsevier GmbH。版权所有。

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