Relatively small motion measurement errors manifest themselves principally as a phase error in Synthetic Aperture Radar (SAR) complex data samples, and if large enough become observable as a smearing, blurring, or other degradation in the image. The phase error function can be measured and then deconvolved from the original data to compensate for the presumed motion error, ultimately resulting in a well-focused image. Techniques that do this are termed “autofocus” algorithms. A very popular autofocus algorithm is the Phase Gradient Autofocus (PGA) algorithm. The nearly universal, and typically reasonable, assumption is that the motion errors are less than the range resolution of the radar, allowing solely a phase correction to suffice.
Very large relative motion measurement errors manifest themselves as an unexpected additional shifting or migration of target locations beyond any deterministic migration during the course of the synthetic aperture. Degradation in images from data exhibiting errors of this magnitude are substantial, often rendering the image completely useless. When residual range migration due to either real or apparent motion errors exceeds the range resolution, conventional autofocus algorithms fail.
Excessive residual migration is increasingly encountered as resolutions become finer, less expensive inertial sensors are used, and operating ranges become longer (due to atmospheric phenomena).
A new migration-correction autofocus algorithm has been developed that estimates the excessive residual migration and applies phase and frequency corrections to properly focus the image. This overcomes the conventional constraint that motion errors not exceed the SAR range resolution.