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Robust DOA estimation and array calibration in the presence of mutual coupling for uniform linear array

机译:在存在均匀线性阵列互耦的情况下进行可靠的DOA估计和阵列校准

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摘要

The presence of unknown mutual coupling between array elements is known to significantly degrade the performance of most high-resolution direction of arrival (DOA) estimation algorithms. In this paper, a robust subspace-based DOA estimation and array auto-calibration algorithm is proposed for uniformly linear array (ULA), when the array mutual coupling is present. Based on a banded symmetric Toeplitz matrix model for the mutual coupling of ULA, the algorithm provides an accurate and high-resolution DOA estimate without any knowledge of the array mutual couplings. Moreover, a favorable estimate of mutual coupling matrix can also be achieved simultaneously for array auto-calibration. The algorithm is realized just via one-dimensional search or polynomial rooting, with no multidimensional nonlinear search or convergence burden involved. The problem of parameter ambiguity, statistically consistence and efficiency of the new estimator are also analyzed. Monte-Carlo simulation results are also provided to demonstrate the effectiveness and behavior of the proposed algorithm.
机译:已知数组元素之间存在未知的相互耦合会大大降低大多数高分辨率到达方向(DOA)估计算法的性能。本文提出了一种在阵列相互耦合的情况下,针对均匀线性阵列(ULA)的基于子空间的鲁棒DOA估计和阵列自动校准算法。基于用于ULA相互耦合的带状对称Toeplitz矩阵模型,该算法无需对阵列相互耦合有任何了解即可提供准确且高分辨率的DOA估计。此外,对于阵列自动校准,也可以同时获得互耦矩阵的有利估计。该算法仅通过一维搜索或多项式求根来实现,不涉及多维非线性搜索或收敛负担。还分析了新估计量的参数歧义,统计一致性和效率问题。还提供了蒙特卡洛仿真结果,以证明所提出算法的有效性和行为。

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