Nowadays, high-speed sampling and transmission is a foremost challenge of radar system.
In order to solve this problem, a compressive sensing approach is proposed for radar
target signals in this study. Considering the block sparse structure of signals, the
proposed method uses a simple measurement matrix to sample the signals and employ
a Block Sparse Bayesian Learning (BSBL) algorithm to recover the signals. The classical
BSBL algorithm is applicable to real signal, while radar signals are complex. Therefore,
a Complex Block Sparse Bayesian Learning (CBSBL) is extended for the radar target
signal reconstruction. Since the existed radar signal compressive sensing models do
not take block structures in consideration, the signal reconstruction of proposed
approach is more accurate and robust, and the simple measurement matrix leads to an
easy implementation of hardware. The effectiveness of the proposed approach is demonstrated
by numerical simulations.