Joint Two-Dimensional DOA and Frequency Estimation for L-Shaped Array via Compressed Sensing PARAFAC Method

Abstract

In this paper, we combine the compressed sensing theory with the parallel factor (PARAFAC) model to present a 2-D direction of arrival (2D-DOA) and a frequency estimation algorithm for an L-shaped array. We first build the multi-delay outputs data as the PARAFAC model, then compress it with partitioning and perform the PARAFAC decomposition through a trilinear alternating least square algorithm. Finally, we reconstruct the received data with sparsity to obtain the automatically paired 2D-DOA and frequency. The proposed algorithm is effective for both uniform and non-uniform L-shaped array, and owing to the compression process, it holds the properties of lower computational complexity and smaller capacity for data storage, compared with a traditional PARAFAC algorithm. The angle and frequency estimation performance of the proposed algorithm is close to the traditional PARAFAC method, and outperforms the estimating signal parameters via a rotational invariance techniques algorithm and a propagator method. Simulation results verify the effectiveness and superiority of our approach.