UAV-Borne 2-D and 3-D Radar-Based Grid Mapping
Philipp Hügler, Timo Grebner, Christina Knill, Christian Waldschmidt
Abstract
For unmanned aerial vehicles (UAVs), grid maps can be a versatile tool for navigation and self-localization. In general, payload is critical for UAVs and every additional sensor limits the flight duration. Due to its robustness and the ability to directly measure velocities, radar sensors are well suited for sense and avoid applications (SAAs) for UAVs. It would be advantageous if these sensor data could be used to generate grid maps instead of mounting additional sensors such as light detection and ranging (LiDAR). This letter demonstrates that using the data from high-resolution multiple-input–multiple-output (MIMO) imaging radars, high-resolution 2-D and 3-D radar grid maps can be created. The necessary adaption of the sensors free-space model for MIMO radar-based occupancy grid maps is presented in detail. UAV-borne measurements resulting in 2-D and 3-D grid maps with an adequate representation of the environment validate this approach.