Enhancement of inverse synthetic aperture radar image using convolved high-order instantaneous moment

Abstract

In this paper, we consider the generation of inverse synthetic aperture radar (ISAR) image of a target using polynomial phase signal (PPS) modeling of time histories. For a target under complex motion, the time histories in the backscatter signal with time-varying Doppler frequency shifts are modeled as multicomponent PPS. We propose the convolution of scaled high-order instantaneous moments to enable the use of high resolution spectral estimators, such as estimation of signal parameters via rotational invariance technique (ESPRIT), for estimation of the parameters of the multicomponent PPS. Using the proposed technique, the phase parameters are estimated with enhanced resolution and improved accuracy in terms of the MSE of the estimates, as compared to the conventionally used Fourier transform based method, for the considered multicomponent signal in medium to high signal-to-noise ratio. The proposed technique is utilized in ISAR imaging to achieve highly focused image of the target.