Compressive Sensing Based 3D SAR Imaging with Multi-PRF Baselines

In this paper, we fundamentally re-examine 3D SAR imaging and propose a CS-based approach aiming to reduce the data collection cost and increase the elevation resolution. In particular, our approach significantly reduces the number of baselines required to acquire the scene of interest, as well as the pulsing rate in each baseline. The baselines are collected using multiple passes of a single or multiple SAR platforms such that their elevations are randomly distributed in the available elevation space. Each baseline uses a fixed pulse repetition frequency (PRF) which can be different from the PRFs used in other baselines. Using the collected multi-baseline data in its entirety we generate a high resolution 3D reflectivity map, using a CS-based iterative imaging algorithm. Our simulation results demonstrate that the proposed method can improve elevation resolution significantly by fusing data from multiple platforms due to the very large virtual elevation aperture even with a small number of baselines.