Underdetermined Low-Complexity Wideband DOA Estimation with Uniform Linear Arrays
Hantian Wu, Qing Shen, Wei Liu, Wei Cui
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For a uniform linear array (ULA) with specially designed spacing and system settings, the received signals are first decomposed into different frequency bins via discrete Fourier transform (DFT). By grouping the frequencies of interest into several pairs, a generalized complexity reduction method is proposed to merge the redundant entries in both the auto-correlation matrices at each frequency and the cross-correlation matrices across different frequencies, followed by the group sparsity based low-complexity method to find the directions of arrival (DOAs) of the impinging signals. Simulation results demonstrate that significantly reduced complexity and improved performance can be achieved by the proposed method.