Two-dimensional joint DOA estimation of coherent signals in distributed arrays
Y F Li, Haihong Tao, Haiyun Liao, Han Cao · IET conference proceedings. · 2026
To address the two-dimensional joint direction of arrival (DOA) estimation problem for coherent signal sources in distributed array systems, this paper proposes an multi-criteria stopping orthogonal matching pursuit algorithm (MS-OMP). The algorithm employs a distributed array structure composed of three subarrays, utilizing the high spatial resolution of large aperture arrays and the sparse reconstruction characteristics of the OMP algorithm to achieve effective separation of coherent signals through geometric differences in spatial steering vectors. The algorithm constructs a two-dimensional angle overcomplete dictionary, transforming the coherent signal DOA estimation into a sparse reconstruction problem. Meanwhile, to address the deficiencies of traditional OMP algorithms in multi-signal reconstruction, such as single convergence criteria and imperfect stopping rules, this paper introduces multi-criteria stopping strategies including residual threshold, maximum number of iterations, and minimum residual change. This improved scheme requires no prior knowledge of the number of signals, effectively prevents overfitting, and significantly enhances the algorithm's adaptability. Simulation results demonstrate that the proposed algorithm can successfully achieve two-dimensional DOA estimation of coherent signals under unknown target numbers, and exhibits higher accuracy than traditional OMP algorithms under low signal-to-noise ratio(SNR) conditions.