Abstract:

Due to lack of sparsity information, the orthogonal matching pursuit (OMP) algorithm must set a redundant support in advance, which leads to heavier computation burden, lower noise suppressive ability and poor signal reconstruction performance. This paper proposes a modified Bayesian orthogonal matching pursuit(BOMP)algorithm. Meanwhile, the CramerRao lower bound (CRLB) of the estimated signal is analyzed. Finally BOMP is used for inverse synthetic aperture radar (ISAR) imaging. Theoretical analysis and simulation results show that the proposed algorithm can improve the noise suppressive ability and reconstruction accuracy， and decrease the computing complexity obviously.