Compressive Sensing Based Algorithm for Rotational Motion Estimation and Compensation for ISAR Imaging

摘要

Inverse Synthetic Aperture Radar Imaging (ISAR imaging) is a tool for obtaining a radar image of a target from the received signal after illuminating the target. Typically, the targets of interest are non cooperative, this means that their relative motion with respect to the observing radar is not known a priori. Compensation for the unknown target motion is essential for imaging quality. In this paper we present an algorithm that uses Compressive Sensing(CS) as a leverage to reconstruct the Range Profiles (RP) with finer resolution followed by a technique to estimate the rotational motion parameters using the contribution of all of the scatterers. We call the algorithm CS-RP-RMC.