Distributed Automotive Radar Multi-Modal Sensing

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

Abstract

The drive towards higher levels of autonomy requires accurate perception of vehicle surroundings that can be achieved through distributed sensor network. This paper presents a technique of multi-modal sensing with heterogeneous radar sensors using multiple-input, multiple-output and Doppler beam sharpening (DBS) based beamforming. This provides an enhanced azimuth resolution and wide coverage around the vehicle. DBS has a fundamental limitation of reduced field of view (FoV) that depends on platform velocity. Based on radar data replication, unambiguous FoV has been extended to provide higher level of detail about the vehicle. Presented approach has been validated with experimental data gathered using 77 GHz radar chipsets mounted in forward-looking and corner-looking orientations with respect to the platform trajectory.
Original languageEnglish
Title of host publication2023 20th European Radar Conference (EuRAD)
PublisherIEEE
Number of pages4
ISBN (Electronic)9782874870743
ISBN (Print)9798350322460
DOIs
Publication statusPublished - 26 Oct 2023
Event20th European Radar Conference (EuRAD 2023) - Berlin, Germany
Duration: 20 Sept 202322 Sept 2023

Publication series

NameEuropean Radar Conference (EURAD)

Conference

Conference20th European Radar Conference (EuRAD 2023)
Abbreviated titleEuRAD 2023
Country/TerritoryGermany
CityBerlin
Period20/09/2322/09/23

Bibliographical note

Acknowledgment:
This work is part of the ongoing project ‘Sub-THz Radar sensing of the Environment for future Autonomous Marine platforms - STREAM’ funded by EPSRC UK grant EP/S033238/1.

Keywords

  • automotive radar
  • co-registration
  • corner looking
  • distributed sensors
  • forward looking
  • MIMO-DBS
  • multi-modal

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