A novel structured sparsity-driven autofocus algorithm is proposed based on sparse Bayesian framework.

To accelerate convergence rate of the algorithm, we propose to adaptively eliminate noise-only range cells in phase error estimation stage.

The proposed algorithm can obtain more concentrated images with much smaller number of iterations, particularly in low SNR and highly under-sampling scenarios.