Onboard Radar Processor Development for Rapid Response to Natural Hazards

Abstract

The unique capabilities of imaging radar to penetrate cloud cover and collect data in darkness over large areas at high resolution makes it a key information provider for the management and mitigation of natural and human-induced hazards. Researchers have demonstrated the use of UAVSAR data to determine flood extent, forest fire extent, lava flow, and landslide. Data latency of at most 2–3 h is required for the radar data to be of use to the disaster responders. We have developed a UAVSAR on-board processor for real time and autonomous operations that has high fidelity and accuracy to enable timely generation of polarimetric and interferometric data products for rapid response applications. This on-board processor design provides a space-qualification path for technology infusion into future space missions in a high-radiation environment with modest power and weight allocations. The processor employs a hybrid architecture where computations are divided between field-programmable gate arrays, which are better suited to rapid, repetitious computations, and a microprocessor with a floating-point coprocessor that is better suited to the less frequent and irregular computations. Prior to implementing phase preserving processor algorithms in FPGA code, we developed a bit-true processor model in MATLAB that is modularized and parameterized for ease of testing and the ability to tradeoff processor design with performance. The on-board processor has been demonstrated on UAVSAR flights.