A novel method of translational motion compensation for hopped-frequency ISAR imaging

Abstract

With adoption of the hopped-frequency pulse waveform to inverse synthetic aperture radar (ISAR), a novel method for motion compensation in ISAR imaging, named the minimum waveform entropy method of parameter estimation, is proposed. A measure function, called the waveform entropy, is employed to measure the effects of target motion on both Doppler amplitude spectra and slant range profiles. The method can achieve optimal estimation of motion parameters of a target based on the minimum waveform entropy rule. In addition, the method converts a two-dimensional search for the velocity and acceleration of a target into two one-dimensional searches for the velocity and acceleration respectively, which greatly decreases computational cost, and conveniently realizes real-time processing. Simulation results indicate that the method can accomplish accurate estimation of motion parameters of a target with a good anti-noise performance, thus making it possible to image a target in clutter background.