Regularization Analysis of SAR Superresolution

Abstract

Superresolution concepts offer the potential of resolution beyond the classical limit. This great promise has not generally been realized. In this study we investigate the potential application of superresolution concepts to synthetic aperture radar. The analytical basis for superresolution theory is discussed. In a previous report the application of the concept to synthetic aperture radar was investigated as an operator inversion problem. Generally, the operator inversion problem is ill posed. This work treats the problem from the standpoint of regularization. Both the operator inversion approach and the regularization approach show that the ability to superresolve SAR imagery is severely limited by system noise.-4 - ACKNOWLEDGEMENTS

Sidelobe Suppression with Resolution Maintenance for SAR Images via Sparse Representation

“…In Reference [ 8 ], the method of signal denoising through sparse reconstruction was promoted, in which a unitary dictionary was applied for sparse representation. Furthermore, much attention has been paid to the field of super-resolution of SAR imaging [ 11 , 12 , 13 ], which is another major application of sparse reconstruction. All of the above applications are based upon the sparse prior of a SAR image.…”