A Root-RARE Algorithm for DOA Estimation with Partly Calibrated Uniform Linear Arrays

Zhongchi Fang, Zheng Cao, Lan Wang
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Abstract

The rank-reduction (RARE) algorithm is a well-known class of algorithms for direction of arrival (DOA) es-timation in the presence of imperfect array manifolds. Since the spectral peak search is inevitable for the current RARE algorithm, it may bring a huge occupational load for practical implementations. In order to reduce the computational com-plexity, in this paper, we propose a root-RARE algorithm for DOA estimation with partly calibrated uniform linear arrays (ULAs). Through replacing the spectral peak search with a polynomial root finding, our proposed method can get much higher efficiency than the original RARE method. Simulation results demonstrate that our method can significantly reduce the computational complexity and improve the DOA estimation performance in a low SNR case.
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部分校准均匀线性阵列的方位估计的根-稀有算法
秩约简(RARE)算法是一类著名的不完全阵列流形下的到达方向(DOA)估计算法。由于目前的RARE算法不可避免地要进行谱峰搜索,这可能会给实际实现带来巨大的职业负荷。为了降低计算复杂度,本文提出了一种基于部分校准均匀线性阵列(ula)的DOA估计的根-稀有算法。通过将谱峰搜索替换为多项式寻根,可以获得比原始RARE方法更高的效率。仿真结果表明,在低信噪比情况下,该方法可以显著降低计算复杂度,提高DOA估计性能。
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