A Low-Complexity 2D-DOA Estimation Algorithm with Massive URA

Abstract

Conventional Direction of Arrival (DOA) estimation algorithms, such as Multiple Signal Classification (MUSIC), Root-MUSIC, and Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithms, are difficult to apply to large-scale antenna arrays. Because these algorithms not only require a lot of snapshots of the received data, but also the hardware equipment cannot meet the algorithm complexity requirements. This paper presents a low-complexity DOA estimation algorithm for large-scale Uniform Rectangle Array (URA). We first obtain coarse initial DOA estimates via the two-dimensional fast Fourier transform and then search for the accurate estimates within a very small region. The proposed algorithm only needs one snapshot of the received data to obtain the estimation accuracy of the traditional algorithm. The algorithm also has good robustness, and it can estimate DOA accurately even under extremely low signal-to-noise ratio and many sources. Theoretical results and numerical simulations are provided to assess the superiority of the proposed algorithm.