A CSAR 3D Imaging Method Suitable for Edge Computation

Due to the large amount of CSAR echo data carried by UAVs, either original need be transmitted ground for processing or post-processing must implemented after flight. Therefore, it is difficult use edge computing power such as a UAV onboard computer implement image processing. The commonly used back projection (BP) algorithm and corresponding improved imaging algorithms require computation have slow speed, which further limits realization 3D on nodes. To improve speed imaging, this paper proposes method suitable computation. Firstly, Crazy Climber extracts sine track ridges that represent amplitude changes in range-compressed echo. Secondly, two-dimensional (2D) profiles with different heights are obtained via inverse Radon transform (IRT). Thirdly, Hough extract intersection points defocused circle along X Y directions. Finally, point cloud extraction completed through voting screening. In paper, detection methods ridge extraction, IRT, replace phase compensation traditional BP method, significantly reduces time imaging. correctness effectiveness proposed verified results simulated ideal targets X-band outfield flight raw small rotor unmanned aerial vehicle (SRUAV). provides new direction fast nodes, aircraft terminals. can directly transmitted, information transmission efficiency Internet Things (IoT).