A novel autofocusing algorithm for ISAR imaging based on sparsity-driven optimization
A novel algorithm of phase adjustment joint with ISAR imaging based on sparsity-driven is proposed in this paper. In the scheme, both phase adjustment and imaging are established in an optimization problem to seek for phase errors and reconstruct ISAR image by exploiting the prior sparsity of target scattering field. The novelty of this method lies in its capability of de-noising and overcoming phase errors, resulting in well-focused image. Besides, the optimization problem is solved by using fast Fourier transform and matrix Hardmard multiplication, promoting the efficiently. The experimental results using both simulated data and measured data confirm the validation of the proposal.