Two-dimensional DOA Estimation Based on Compressed Sensing Theory

Two-dimensional direction of arrival (DOA) estimation has been widely used in radar detection, electronic reconnaissance, medical imaging and other fields. Aiming at the problems of inadequate estimation accuracy and enormous computational load of existing algorithms, a DOA estimation algorithm for two-dimensional uniform L-shaped array signals was presented in this paper based on compressed sensing theory. First, an over-complete redundant dictionary was established by using the space frequency of the azimuth angle and pitch angle. Then the orthogonal Gaussian random matrix was used to construct the measurement matrix. Finally, azimuth and elevation were restored by improving RM-FOCUSS algorithm and solving trigonometric function. The theoretical research shows that the proposed method has higher estimation accuracy and resolution than the traditional algorithm under the conditions of high SNR and multi-snapshot, and it reduces the computational complexity by compressing sampling. The simulation results verify the effectiveness and correctness.