SE-Workbench-RF: Performant and High-Fidelity Raw Data Generation for Various Radar Applications

Abstract

Guidance of weapon systems relies on sensors to analyze targets signature. Defense weapon systems also need to detect and then identify threats also using sensors. One important class of sensors is radar systems that are very efficient for all weather detection. High frequency radars can produce high quality images with very complex features such as dihedral and corner reflector high scattering contributors, shadows and layover effects. Besides, image quality is very dependent on the carrier velocity and trajectory. Such sensors systems are so complex that they need simulation to be tested in a large variety of operational conditions. This paper presents a state-of-the-art solution, called SE-Workbench-RF, for generating raw data dedicated to radar simulation based on the exploitation of synthetic environments, which means physical modelling of targets and backgrounds (terrains, buildings, vegetation and other entities). The paper gives an overview of the models and their implementation in SE-RAY-EM, which is the rendering module of SE-Workbench-RF, including specific features related to radar simulation in the maritime environment with targets moving on the dynamic sea surface. Several technical topics are also discussed, such as the rendering technique (ray tracing vs. rasterization), the implementation (CPU vs. GP GPU) and the tradeoff between physical accuracy and computational performance.