Nonparametric Full-Aperture Autofocus Imaging for Microwave Photonic SAR

The microwave photonic synthetic aperture radar (SAR) is capable of realizing large scene remote sensing observation with centimeter or even millimeter resolution, which greatly enhances the ability to acquire target information. A key issue in airborne microwave photonic SAR imaging is how to accurately correct the two-dimensional (2-D) spatial variation characteristic of the motion error. The typical two-step motion compensation (MoCo) method cannot correct the azimuth spatial variant characteristic of motion error, and the traditional subaperture methods may introduce the problems of grating lobes and image stitching. In addition, the efficiency of existing parametric full-aperture autofocus methods is usually low. To solve the above problems, a nonparametric full-aperture autofocus method based on a two-stage processing framework is proposed in this article. The first stage is to introduce a nonparametric low-order nonlinear chirp scaling (NCS) or resampling (RS) model to compensate for the low-order spatial variant motion error that accounts for the dominant component before the range cell migration correction (RCMC), which ensures that there is no significant residual RCM after the RCMC. The second stage introduces a nonparametric high-order NCS/RS model after the RCMC to compensate for the remaining high-order azimuth spatial variant phase error to achieve accurate azimuth focusing. Based on the full-aperture processing strategy, the algorithm proposed in this article avoids the problems existing in the subaperture methods. In addition, the nonparametric modeling is used throughout the autofocus processing (e.g., motion error estimation and parameter reversion of NCS/RS model), which greatly improves the efficiency of autofocus processing. The results of processing simulated and measured data verify the effectiveness of the proposed algorithm.