- "Compressive Tomographic Radar Imaging with Total Variation Regularization", International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), DOI: 10.1109/CoSeRa.2016.7745712, pp. 120-123, September 2016. ,
We consider the problem of compressive imaging of a three-dimensional (3D) scene using multiple observations collected from parallel baselines, formed by monostatic sensors moving in space. In particular, we present a novel iterative imaging method based on the Omega-K algorithm with edgepreserving 3D total variation (TV) regularization. The method combines joint processing of multi-baseline data with TV minimization in a computationally efficient way, thus enabling highresolution imaging of the reflectivity map of the scene. We demonstrate the potential of our method through numerical evaluations on simulated data with noise.