Dictionary Based Sparsity Driven Algorithm for Phase Error Correction in SAR Image Formation

Synthetic Aperture Radar (SAR) is an advanced - active remote-sensing sensor for navigation systems. This sensor produced high resolution 2-D images of the ground. The quality of reconstructed / enhanced images is dependent to the accuracy of the observation model and prior knowledge about the scene. Recently, a lot of attention has been given to the images produced by SAR. Inaccuracies in the observation model of the SAR due to inaccuracies of the velocity and position of the platform, causing degradation of the reconstructed image, necessitates the use of autofocus algorithms. Recently, developed sparse representation-based framework used in SAR image formation, is capable of using the prior knowledge for producing high-quality feature-enhanced images. In this paper we propose a new signal processing algorithm for joint SAR image formation and autofocus in a dictionary-based sparse-representation framework. This new algorithm produces high quality images in presence of observation inaccuracies for any scene that have a sparse representation in a proper dictionary

Dictionary Based Sparsity Driven Algorithm for Phase Error Correction in SAR Image Formation Keywords:

Navigation , Synthetic Aperture Radar (SAR) , Sparsity , Sparse Driven Autofocus (SDA) , Dictionary-Based Sparse Driven Autofocus (DBSDA)