SHARPNESS BASED AUTOFOCUS FOR NON-COOPERATIVE MOVING TARGETS IN SAR DATA

Abstract

Synthetic aperture radar (SAR) imaging of stationary scenes relies on known geometry to form focused images. When a distributed target is moving, the mismatch between assumed and actual target kinematics causes displacement and blur of the target in the image. While various inverse SAR (ISAR) autofocus techniques exist that compensate for target motion, each is tailored to specific operational constraints. This thesis proposes a parametric image-sharpness-based autofocus technique for ground-based non-cooperative moving targets, using the backprojection algorithm. The proposed approach presents motion compensation as a two-parameter image sharpness optimization over target range acceleration and rotation rate. Translational motion compensation (TMC) is first achieved by integrating along the target's slow-time range profile via a range-acceleration search. Subsequently, rotational motion compensation (RMC) addresses target rotation relative to the radar through a rotation-rate search. The proposed method is validated on synthetic SAR data and applied to measured data.