Compressed Sensing Based DOA Estimation Algorithm

Direction of arrival (DOA) estimation plays a very important role in signal processing, it has been widely used in various fields. This paper proposes a DOA estimation method based on compressed sensing. Firstly, we constructed the sparse model of the signal, and obtained the reduced dimension representation of the high-dimensional signal. Then, the orthogonal matching pursuit (OMP) algorithm and L1-SVD algorithm based on singular value decomposition (SVD) are used to reconstruct the signal. Compared with the traditional algorithm, we findthat the introduction of compressed sensing theory into DOA estimation can not only improve the estimation performance, but also reduce the computational complexity, which is a very important topic.