Performance Synthesis of UAV Trajectories in Multistatic SAR

We develop guidelines for the design and analysis of unmanned aerial vehicle (UAV) trajectories for the purpose of high-quality image reconstructions based on a tomographic framework for a downlooking multistatic SAR imaging system. Modern matrix analysis provides several tools to generate performance bounds, which we relate to physical parameters of the synthetic aperture radar (SAR) measurement process. Both deterministic and random trajectories are considered. We apply a central result of random matrix theory to describe the system performance of random-location sampling.