Underdetermined DOA Estimation for Uniform Circular Array Based on Sparse Signal Reconstruction

摘要

This paper proposes a novel sparsity-aware method that can estimate more sources than the number of sensors available based on the l_1 optimization technique. This approach enforces sparsity by l_1 penalization and restricting error by l_2-norm which enables the reconstruction of sparse signals. By using the Khatri-Rao (KR) subspace approach, we obtain an increase in the degrees of freedom (DOFs). Thus, using uniform circular array (UCA), we can perform underdetermined DOA estimation for sparse signals. Simulation results confirms the effectiveness of the proposed method.