Fast Ambiguity-Free Subspace-Based Multiple AoA Estimation for Hybrid Linear Arrays
Wei-Cheng Kao, Jwo-Yuh Wu, Shang-Ho Lawrence Tsai, Tsang-Yi Wang · 2023
Angle-of-arrival (AoA) estimation via hybrid uniform linear arrays is subject to inherent ambiguity incurred by mixing many subarray measurements into just few RF chains. With the aid of non-uniform subarray placement, this paper proposes a low-complexity beam-space MUSIC algorithm capable of achieving ambiguity-free multiple AoA estimation. An ambiguity-free condition, specified by inter-subarray spacings, is derived, leading to various array configurations guaranteeing unique AoA recovery. Simulation results show that our proposed approach compares favorably with an existing temporal-domain based MUSIC method at reduced computational complexity.