Radar signal reconstruction algorithm based on Complex Block Sparse Bayesian Learning

Sparse signal reconstruction is one core technology of Radar compressive sensing. Algorithms based on Sparse Bayesian Learning are the focus of study in recent years, because of their good reconstruction preferment. Signal reconstruction algorithm base Block Sparse Bayesian Learning (BSBL) frame is excellent for reconstructing signals of block sparse structure. It exploits not only the block sparse structure of signals, but also the correlation inside the block to improve the accuracy of reconstruction. But, classical BSBL algorithm is proposed for real signals. So, it cannot reconstruct complex signal directly. This paper extended the BSBL frame and reconstruction algorithm based on BSBL frame into complex number domain. The extended signal reconstruction algorithm based on Complex Block Sparse Bayesian Learning (CBSBL) frame can deal with complex signals directly. And then CBSBL algorithm was applied to reconstruct radar complex signals. Experimental results showed that the CBSBL algorithm is effective and efficient.