Efficient 2D DOA Estimation via Decoupled Projected Atomic Norm Minimization

• DOI: 10.3390/electronics13050846
• Publication Date: 2024-02-22T16:28:47Z
• Authors: Mingming Liu; Yangyang Dong; Chunxi Dong; Guoqing Zhao
• Keywords: Smoothing; Minification

This paper presents an efficient two-dimensional (2D) direction of arrival (DOA) estimation method, termed as decoupled projected atomic norm minimization (D-PANM), to solve the angle-ambiguity problem. It first introduces a novel metric via projecting original atom set onto smoothing space, based on which we formulate equivalent semi-definite programming (SDP) Then, two relatively low-complexity Toeplitz matrices can be obtained estimate DOAs. We further exploit structural information hidden in newly constructed data avoid pair matching for azimuth and elevation angles when number sensors is odd, then propose fast feasible alternating projections (D-AP) algorithm, reducing computational complexity great extent. Numerical simulations are performed demonstrate that proposed algorithm no longer restricted by angle ambiguity scenarios, but instead provides more stable performance, even multiple signals share same both dimensions. Additionally, it greatly improves resolution, with control computation load compared existing (ANM) algorithm.