DOA Estimation of Time-Modulated Linear Array Based on Sparse Signal Recovery

Under the circumstances of small number of snapshots, low signal-to-noise ratio, and closely spaced sources, especially with correlated signals, the existing direction of arrival angle (DOA) estimation methods for time-modulated linear arrays (TMLAs) generally does not yield satisfactory results. To dealwith those problems, a new weighted l1-norm DOA estimation algorithm is proposed for the TMLA in this letter. The proposed algorithm constructs the weighted matrix by making full use of the orthogonality of the signal subspace and the noise subspace to penalize the l1-norm constrained model. Accordingly, the reconstructed coefficient vector with better sparsity could be achieved, and the false peaks could be effectively suppressed. Simulation results have been provided to validate the effectiveness of the proposed method.