Abstract:

In order to obtain fast inverse synthetic aperture radar (ISAR) sparse images with finite pulse, a multiple measurement vectors (MMV) model block sparse signal recovery ISAR imaging algorithm is proposed by utilizing the block structure of targets. Firstly, the MMV sparse imaging model is established, ISAR imaging is converted into the MMV block sparse signal recovery problem. Then, one negative exponential function sequence is used as the smoothed function to approach the block L₀ norm, the optimization solution of the smoothed function is obtained by constructing a decreasing sequence, the solution is projected into the feasible set by the gradient projection algorithm. Finally, the revised step is added to ensure the searching direction of the optimization value of the block sparse signal is the steepest descent gradient direction. Simulation results verify the proposed algorithm has advantages in imaging time and imaging quality.