Sparse Representation-Based Method for Two-Dimensional Direction-of-Arrival Estimation with L-Shaped Array

A novel sparse representation-based method for two-dimensional (2-D) direction-of-arrival (DOA) estimation with L-shaped array is proposed. In our method, the 2-D DOA estimation is cast as a reconstituted problem of sparse matrix. The model for sparse-matrix reconstitution is first presented based on the cross-correlation matrix. Then an extended orthogonal matching pursuit (EOMP) algorithm is put forward to reconstitute the sparse matrix. With the use of the model for sparse-matrix reconstitution and EOMP algorithm, pair matching is no longer required in our method, and the estimation accuracy of our method is higher than the existing subspace-based and sparse representation-based methods. The simulation results demonstrate the effectiveness and efficiency of the proposed method.