In this thesis, we consider the problem of joint image enhancement of multi-channel Synthetic Aperture Radar (SAR) data. For multi-channel data, we show that independent enhancement of each channel degrades the relative phase information across channels that is useful for 3D reconstruction of targets.
We formulate a joint enhancement problem to simultaneously enhance multi-channel SAR data while preserving the common support and the cross-channel phase information. We pose this problem as a joint optimization problem with constraints on pixel magnitudes and propose three methods for solving it. The proposed algorithms are applied to both synthetic data and Xpatch synthetic radar scattering prediction data of a backhoe. The resulting sparse images are found to preserve the relative phase information required for 3D reconstruction. Finally we derive the Cramér-Rao bound for the relative phase error and compare the accuracy of the independent and the joint enhancement approaches to that bound.