A robust autofoeus approach, referred to as AUTOCLEAN (AUTOfoCUS via CLEAN), is proposed for the motion compensation in ISAR (inverse synthetic aperture radar) imaging of moving targets. It is aparametric algorithm based on a very flexible data model which takes into account arbitrary range migration and arbitraryphase errors acrossthe synthetic aperture thatmaybeinduced by unwanted radialmotion of the target as well as propagation or system instabifity. AUTOCLEAN can bedassifiedus amultiple scatterer algorithm (MSA), but itdiffers considerablyfrom 0tller existing MSAs in several aspects.1) Dominant scatterers are selected automatically in the two-dimensional (2-D) image domain;2) scatterers may not be well isolated or verydominant;3) phase and RCS (radar Cross section) informationfrom each seiected scattererare eombined inan optimalway;4) the troublesome phase unwrapping step is avoided. AUTOCLEAN is computationally efficient and involves only a sequence of FFTs (fast Fourier transforms). Another goodfeature associated with AUTOCLEAN is that its performance can beprogressively improved by assumingalarger number of dominant scatterers for the target. Numerical and experimental results hare shown that AUTOCLEAN is a very robust autofoCus tool for ISAR imaging.