Joint time-frequency ISAR using adaptive processing

Abstract

A new joint time-frequency inverse synthetic aperture radar (ISAR) algorithm that combines ISAR processing with the joint time-frequency signal representation is presented as a means of extracting the nonpoint-scattering features from the standard ISAR image. The adaptive Gaussian representation, applied to the range aids of the ISAR image, is used as the time-frequency processing engine. This technique uses Gaussian basis functions to adaptively parameterize the data and, as a consequence, the point-scattering mechanisms and resonance phenomena can be readily separated based on the width of the Gaussian bases. The adaptive joint time-frequency ISAR algorithm is tested using data generated by the moment-method simulation of simple structures and the chamber measurement data from a scaled model airplane. The results show that nonpointscattering mechanisms can be completely removed from the original ISAR image, leading to a cleaned image containing only physically meaningful scattering centers. The nonpoint-scattering mechanisms, when displayed in the frequency-aspect plane, can be used to identify target resonances and cutoff phenomena.