An Improved Phase Gradient Autofocus Algorithm For ISAR Phase Autofocus Problem

Abstract

Abstract The Phase Gradient Autofocus Algorithm (PGA) is widely used in radar imaging due to its ability to achieve high accuracy estimation of phase error of arbitrary orders. However, in inverse synthetic aperture radar (ISAR) imaging, the target usually occupies continuous range bins and there may be multiple stronger scatters in a range bin. In this case, the range bins selection method of the conventional algorithm tends to miss a part of the useful data contained in the target, and its windowing method also tends to cause the loss of useful high-frequency components in the range bins. Aiming at the above problems, an improved PGA algorithm is proposed in this paper. It uses an amplitude-based traversal method and Kaiser window to retain the valid echo data in the target and range bins, and eventually to achieve phase autofocus. Simulation results show that the improved method can obtain more stable and evident focusing results for ISAR target faster than the conventional method.