Parametric translational motion compensation of spaceborne ISAR imagery for earth-orbit targets based on parabola detection and entropy minimization

Abstract

ABSTRACT In the spaceborne inverse synthetic aperture radar (ISAR) imagery for space targets, the noise environment can be worse than traditional imaging scenarios because of the signal decay caused by the long radial range. Parametric translational motion compensation (TMC) method based on the image quality optimization has been proved to be useful in the low signal-to-noise ratio environments. However, a proper estimation of the initial values is indispensable to avoid local optimum solutions and improve computational efficiency. In this letter, a TMC method based on the parabolic curve detection and the entropy minimization is proposed. An initial compensation result is firstly obtained with the range shifts estimated by the parabolic curve detection using the Hough transform. Further, the minimum entropy-based method is employed to improve compensation accuracy. The imaging results of the real data are provided and compared with other methods to demonstrate the effectiveness and the high accuracy of the proposed method.