2026-09-20T08:53:23Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/116267 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Al-Hassanieh, Haitham 2022-08 application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms The student, Waleed Ahmed, accepted the attached license on 2022-07-18 at 15:24. The student, Waleed Ahmed, submitted this Thesis for approval on 2022-07-18 at 15:40. This Thesis was approved for publication on 2022-07-19 at 08:59. DSpace SAF Submission Ingestion Package generated from Vireo submission #18369 on 2022-11-15 at 18:21:33 Accurate detection for self driving cars using multi-resolution MIMO radar Ahmed, Waleed 2022-07-19 Radar Perception Self-driving Cars Object Detection MIMO Radar mmWave Sensing Automotive Radar Dataset Millimeter wave (mmWave) radars are becoming a more popular sensing modality in self-driving cars due to their favorable characteristics in adverse weather. Yet, they currently lack sufficient spatial resolution for semantic scene understanding. In this thesis, we present Radatron, a system capable of accurate object detection using mmWave radar as a stand-alone sensor. To enable Radatron, we introduce a first-of-its-kind, high resolution automotive radar dataset collected with a cascaded MIMO (Multiple Input Multiple Output) radar. Our radar achieves 5cm range resolution and 1.2 degrees angular resolution, 10x finer than other publicly available datasets. We also develop a novel hybrid radar processing and deep learning approach to achieve high vehicle detection accuracy. We train and extensively evaluate Radatron to show it achieves 92.6% AP50 and 56.3% AP75 accuracy in 2D bounding box detection, an 8% and 15.9% improvement over prior art respectively. Thesis eng https://hdl.handle.net/2142/116267 Copyright 2022 Waleed Ahmed M.S. Thesis Computer Science University of Illinois at Urbana-Champaign Computer Science