Combined MAM-PCA autofocus for stripmap SAR

Abstract

The nonparametric phase curvature algorithm (PCA) is commonly used to estimate residual motion error in stripmap SAR. The algorithm is capable of estimating second and higher order errors, as well as high frequency errors. However, its dependence on dominant scatterers restricts its application to a wide variety of scenes. Such a limitation is encountered in focusing a polarimetric L-band SAR dataset collected from an agricultural field. The lack of dominant scatterers in the scene results in inaccurate error estimation when PCA is applied directly. Another autofocus scheme, the Multi-aperture Mapdrift (MAM), is used first to eliminate the low order motion errors. This improves the focusing quality of the existing targets. The enhanced point targets are then suitable for PCA to remove the remaining higher order motion errors. The novel MAM-PCA combination significantly improves the image contrast compared to that obtained from the approaches applied separately. Point target based comparison of MAM, PCA and MAM-PCA show that the proposed technique improves the overall quality of the target profile.