Radatron: Accurate Detection Using Multi-resolution Cascaded MIMO Radar

Sohrab Madani, Jayden Guan, Waleed Ahmed, Saurabh Gupta, Haitham Hassanieh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 paper, 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 5 cm range resolution and 1.2 angular resolution, 10 × 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 % AP 50 and 56.3 % AP 75 accuracy in 2D bounding box detection, an 8 % and 15.9 % improvement over prior art respectively. Code and dataset is available on https://jguan.page/Radatron/.

Original languageEnglish (US)
Title of host publicationComputer Vision – ECCV 2022 - 17th European Conference, Proceedings
EditorsShai Avidan, Gabriel Brostow, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner
PublisherSpringer
Pages160-178
Number of pages19
ISBN (Print)9783031198410
DOIs
StatePublished - 2022
Event17th European Conference on Computer Vision, ECCV 2022 - Tel Aviv, Israel
Duration: Oct 23 2022Oct 27 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13699 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th European Conference on Computer Vision, ECCV 2022
Country/TerritoryIsrael
CityTel Aviv
Period10/23/2210/27/22

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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