Robust autofocus algorithm for ISAR imaging of moving targets

A robust autofocus approach, referred to as AUTOCLEAN (AUTOfocus via CLEAN) , is proposed for the motion compensation in ISAR (inverse synthetic apertu re radar) imaging of moving targets. It is a parametric algorithm based on a very flexible data model which takes into account arbitrary range migrati on and arbitrary phase errors across the synthetic aperture that may be ind uced by unwanted radial motion of the target as well as propagation or syst em instability. AUTOCLEAN can be classified as a multiple scatterer algorit hm (WA), but it differs considerably from other existing MSAs in several as pects. 1) Dominant scatterers are selected automatically in the two-dimensi onal (2-D) image domain; 2) scatterers may not be well isolated or very dom inant; 3) phase and RCS (radar cross section) information from each selecte d scatterer are combined in an optimal way; 4) the troublesome phase unwrap ping step is avoided. AUTOCLEAN is computationally efficient and involves o nly a sequence of FFTs (fast Fourier transforms). Another good feature asso ciated with AUTOCLEAN is that its performance can be progressively improved by assuming a larger number of dominant scatterers for the target. Numeric al and experimental results have shown that AUTOCLEAN is a very robust auto focus tool for ISAR imaging.