A Modified Factorized Geometrical Autofocus Method for Wide Angle SAR

Abstract

Wide-Angle (WA) synthetic aperture radar (SAR) has shown remarkable performance in high-resolution mapping, and its mostly used imaging algorithm, fast factorized back projection (FFBP), is efficient, robust, and of low computational complexity. However, trajectory deviations and the system calibration error, introduced by low measurement accuracy, dramatically degrade FFBP's performance. This article proposes the modified factorized geometrical autofocus (MFGA) method for WA-SAR to address the above problems in FFBP. MFGA implements the phase gradient algorithm on defocus subimages at first. Then, a factorized geometrical error hypothesis between subimages is proposed. And the corresponding defocus factors are classified as three independent parts: image distortion, spectrum migration, and phase error. To deal with those problems, MFGA introduces image registration techniques and a maximum sharpness method to calibrate image distortion and phase error. Moreover, in MFGA, based on minimum entropy and least square method, a Doppler spectrum migration correction algorithm is proposed to correct spectrum migration. In the FFBP chain, MFGA is used on subimages refocus and fusion until obtaining a full-resolution image. In our experiments, we compared MFGA and other time-domain autofocus algorithms using simulated data and real data obtained by helicopter and airship with false trajectory and system calibration parameters. The results show that MFGA performs better in terms of the peak to side-lobe ratio, the azimuth resolution, the refocused images' entropy, and processing time consumption. The better performance demonstrates MFGA's advantages in addressing trajectory deviations and the system calibration error for WA-SAR.

Keywords

• Autofocus
• fast factorized back projection
• phase gradient algorithm
• spectrum migration
• system calibration error
• wide angle synthetic aperture radar