Forward imaging robotic vehicle mission using ultra-wideband synthetic aperture radar

In support of the Army vision for increased mobility, survivability, and lethality, we are investigating the use of ultrawideband (UWB) radar technology to enhance unmanned ground vehicle missions. The ability of UWB radar technology to detect foliage-concealed objects could provide an important obstacle avoidance capability for robotic vehicles, which would improve the speed and maneuverability of these vehicles and consequently increase the survivability of the U.S. forces. This technology would address the particular challenges that confront robotic vehicles such as large rocks hidden in tall grass and voids such as ditches and bodies of water. This paper describes electromagnetic model predictions of the radar cross section of potential robotic vehicle obstacles. These model predictions will be used to generate simulated synthetic aperture radar images based on notional imaging geometries. The simulated images will be used to guide the data collection scenarios for the Army Research Laboratory (ARL) ultra-wideband BoomSAR system. Using a combination of the models, simulations, and BoomSAR data we investigate the operating parameters (imaging angles, frequencies, bandwidth, etc.) for an obstacle-avoidance UWB radar.