An Underdetermined Two-Dimensional DOA Estimation Algorithm for Sparse Circular Arrays

Two-dimensional Direction of arrival (2D DOA) is a challenging problem in sparse circular arrays (SCAs), especially in the field of underdetermined estimation. In this paper, based on sparse signal recovery (SSR) theory, an underdetermined 2D DOA estimation method is proposed for SCAs. The Khatri-Rao (KR) subspace method is introduced to construct a signal model for underdetermined DOA estimation. Then, different from the previous method of converting 2D discrete grids into 1D vectors, a new 2D SSR model based on a 2D over-complete basis is constructed. Finally, an improved algorithm based on the compressed sampling matching pursuit algorithm (CoSaMP) is used to realize SSR and implement underdetermined 2D DOA estimation. Numerical simulation results indicate that the proposed method has excellent DOA estimation accuracy with extremely low complexity.