Full-Aperture Azimuth Spatial-Variant Autofocus Based on Contrast Maximization for Highly Squinted Synthetic Aperture Radar

摘要

Generally, high-resolution imaging for highly squinted synthetic aperture radar (SAR) data is a difficult problem due to large range migration. Thus, when trying to solve this nontrivial problem, an azimuth-variant Doppler will arise, thereby leading to phase errors containing the azimuth spatial-variant (ASV) component. In this article, we analyze the characteristics of highly squinted SAR data and propose a new full-aperture ASV phase error autofocus algorithm. In this new algorithm, the accurate and suitable phase error signal model for highly squinted SAR data is derived. Moreover, the closed-form solution of the relationship between a distorted image and a focused image is also explicitly revealed. Furthermore, in this newly proposed algorithm, an accurate estimation of nonlinear ASV phase error is established based on the maximum contrast of the SAR imagery. In addition, an iterative gradient-based solver is introduced. The advantage of this new method provides a simple yet effective approach while being able to eliminate the ASV phase errors. More importantly, the accuracy of this new method using the full-aperture data is independent of SAR imaging algorithms. As a result, the proposed new method can be easily embedded in many existing imaging algorithms to produce focused imagery. Finally, two real highly squinted SAR data sets are provided to validate the advantages of our algorithm.