Joint Enhancement of Multichannel SAR Data

In this paper we consider the problem of joint enhancement of multichannel Synthetic Aperture Radar (SAR) data. Previous work by Cetin and Karl introduced nonquadratic regularization methods for image enhancement using sparsity enforcing penalty terms. For multichannel data, independent enhancement of each channel is shown to degrade the relative phase information across channels that is useful for 3D reconstruction. We thus propose a method for joint enhancement of multichannel SAR data with joint sparsity constraints. We develop both a gradient-based and a Lagrange-Newton-based method for solving the joint reconstruction problem, and demonstrate the performance of the proposed methods on IFSAR height extraction problem from multi-elevation data.