2021/01/29 by Neeraj Pandey, Pandey, Neeraj, Shobha Sundar Ram +1 · 1 citation
Engineering · #Advanced SAR Imaging Techniques #FOS: Electrical engineering #Microwave Imaging and Scattering Analysis #Radar Systems and Signal Processing #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2101.12535
openalex publication_date 2021/01/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a framework for simulating realistic inverse synthetic aperture\nradar images of automotive targets at millimeter wave frequencies. The model\nincorporates radar scattering phenomenology of commonly found vehicles along\nwith range-Doppler based clutter and receiver noise. These images provide\ninsights into the physical dimensions of the target, the number of wheels and\nthe trajectory undertaken by the target. The model is experimentally validated\nwith measurement data gathered from an automotive radar. The images from the\nsimulation database are subsequently classified using both traditional machine\nlearning techniques as well as deep neural networks based on transfer learning.\nWe show that the ISAR images offer a classification accuracy above 90% and are\nrobust to both noise and clutter.\n