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Computationally Efficient Ambiguity-Free Two-Dimensional DOA Estimation Method for Coprime Planar Array: RD-Root-MUSIC Algorithm
Mathematical Problems in Engineering ( IF 1.430 ) Pub Date : 2020-07-10 , DOI: 10.1155/2020/2794387
Luo Chen 1, 2, 3 , Changbo Ye 1, 2 , Baobao Li 1, 2
Affiliation  

While the two-dimensional (2D) spectral peak search suffers from expensive computational burden in direction of arrival (DOA) estimation, we propose a reduced-dimensional root-MUSIC (RD-Root-MUSIC) algorithm for 2D DOA estimation with coprime planar array (CPA), which is computationally efficient and ambiguity-free. Different from the conventional 2D DOA estimation algorithms based on subarray decomposition, we exploit the received data of the two subarrays jointly by mapping CPA to the full array of the CPA (FCPA), which contributes to the enhanced degrees of freedom (DOFs) and improved estimation performance. In addition, due to the ambiguity-free characteristic of the FCPA, the extra ambiguity elimination operation can be avoided. Furthermore, we convert the 2D spectral search process into 1D polynomial rooting via reduced-dimension transformation, which substantially reduces the computational complexity while preserving the estimation accuracy. Finally, numerical simulations demonstrate the superiority of the proposed algorithm.

中文翻译:

互质平面阵列的高效计算无歧义二维DOA估计方法:RD-Root-MUSIC算法

尽管二维(2D)谱峰搜索在到达方向(DOA)估计中承受着昂贵的计算负担,但我们提出了一种用于二维共面平面阵列的2D DOA估计的二维Root-MUSIC(RD-Root-MUSIC)算法(CPA),它在计算上非常有效且没有歧义。与基于子数组分解的常规2D DOA估计算法不同,我们通过将CPA映射到CPA的整个数组(FCPA)来联合利用两个子数组的接收数据,这有助于增强自由度(DOF)和改进估算效果。另外,由于FCPA的无歧义特性,可以避免额外的歧义消除操作。此外,我们通过降维变换将2D频谱搜索过程转换为1D多项式生根,从而在保持估计精度的同时大幅降低了计算复杂度。最后,数值仿真证明了该算法的优越性。
更新日期:2020-07-10
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