A High-Resolution Airborne SAR Autofocusing Approach Based on SR-PGA and Subimage Resampling With Precise Hyperbolic Model

Abstract

High-resolution airborne synthetic aperture radar imaging requires long synthetic aperture time (LSAT). However, the LSAT invalidates the Fresnel approximation in the traditional autofocusing method, leaving a residual signal phase in the motion error. To solve the problem, a signal-reconstruction-based phase gradient autofocus (SR-PGA) and a subimage resampling (SIR) methods are proposed. They are developed on the hyperbolic model. First, a subaperture division strategy divides the full-aperture high-order error into multiple low-order subaperture errors (SPEs). Then, the SR-PGA is developed to estimate the SPE, in which the precise deramping is reconstructed to eliminate the residual signal phase in the SPE. Third, the SIR is proposed to eliminate residual Doppler-variant shift of the adjacent subimages, improving the accuracy of the SPE combination. Finally, simulation and actual data processing verify the effectiveness and validity of the algorithm.

Keywords

• Doppler subimage resampling
• hyperbolic model
• long synthetic aperture
• SAR autofocusing
• signal-reconstruction-based phase gradient autofocus (SR-PGA)
• synthetic aperture radar (SAR)