In this paper

a novel autofocusing algorithm of inversed synthetic aperture radar (ISAR) imaging based on sparse constraint is proposed

which can be applied in sparse aperture ISAR imaging.In the scheme

taking the phase errors as model errors

the proposed approach exploits the sparsity prior of ISAR image to construct the minimum 1-norm image formation.Then numerical method is adopted to realize adaptive phase error estimation while well-focused ISAR image can finally be obtained.Meanwhile

the objective function of ISAR imaging is established based on matrix model

which can be conveniently solved using fast Fourier transform (FFT) and matrix Hardmard multiplication.Due to the utilization of sparsity restriction

the proposed approach can still be capable of performing well even in the case of low signal-to-noise ratio (SNR).The experimental results using both simulated data and measured data confirm the validation of the proposal.