Reverse Backprojection Algorithm for the Accurate Generation of SAR Raw Data of Natural Scenes

Abstract

Future synthetic aperture radar (SAR) mission concepts often rely on locally nonlinear (e.g., high orbits and bistatic) surveys or acquisition schemes. The simulation of the raw data of natural scenes as acquired by future systems appears as one powerful tool in order to understand the particularities of these systems and assess the impact of system and propagation errors on their performance. We put forward, in this letter, a new formulation of the reverse backprojection algorithm for the accurate simulation of raw data of natural surfaces. In particular, the algorithm is perfectly suited to accommodate any kind (1-D/2-D) of temporal and spatial variation, e.g., in observation geometry, acquisition strategy, or atmospheric propagation. The algorithm is analyzed with respect to its SAR image formation sibling, and tested under different simulation scenarios. We expect the reverse backprojection algorithm to play a relevant role in the simulation of future geosynchronous and multistatic SAR missions.