Research on Compressed Sensing DOA Estimation Based on Priori Space Sparsity of Information Theory

Using spatial sparsity of array signal, compressed sensing technology can be used to model DOA estimation. The matching pursuit algorithm of classical greedy orthogonal is used to solve the problem. However, this algorithm must take spatial sparsity of signal that the number of sources of spatial array signal as a prior condition to accurately estimate multiple DOAs. The AIC and MDL criteria based on information theory are adopted to estimate the spatial sparsity in this paper, and spatial sparse distribution of equal sinusoid is used. Finally better MDL criteria and greedy orthogonal matching pursuit algorithm are combined to solve the problem. The simulation results show that the better performance of direction estimation can be obtained under multiple snapshot data model.