Range-Azimuth-Velocity Image Generation for Perception Applications in VTOL Vehicles Using Echodyne Echoflight Radar

This paper presents a Cartesian range-azimuthvelocity (CRAV) image generation method for the Echodyne EchoFlight radar. The EchoFlight radar provides range-velocity (RV) maps for beam directions defined by a given azimuth (Az) and elevation (El) range. This study focuses on developing a method to process raw RV maps and generate CRAV images. The proposed method significantly optimizes the data storage requirements of the EchoFlight radar for Vertical Takeoff and Landing (VTOL) vehicle applications, while also adapting it for perception tasks in VTOLs. The ultimate objective is to utilize these CRAV images in a radar image enhancement method in future work to achieve improved object representation. The proposed method consists of three main steps. First, RV maps across a selected range of Az and El are collected to construct a range-azimuth-velocity (RAV) matrix. Next, a polar RAV (PRAV) image is generated by summing the RAV matrix along the velocity axis. Finally, the PRAV image is converted into Cartesian format. The results demonstrate that the CRAV images generated using the proposed method effectively capture both static and dynamic objects. Furthermore, the proposed CRAV image generation achieved a 16 times storage reduction compared to storing raw RV maps, making it a practical and efficient solution for VTOL radar perception applications.