Combining automotive radar and LiDAR for surface detection in adverse conditions

Andrew M. Wallace, Saptarshi Mukherjee, Bemsibom Toh, Alireza Ahrabian

Research output: Contribution to journalArticlepeer-review

Abstract

Automotive radar and light detection and ranging (LiDAR) sensors have complementary strengths and weaknesses for 3D surface mapping. We present a method using Markov chain Monte Carlo sampling to recover surface returns from full-wave longitudinal signals that takes advantage of the high spatial resolution of the LiDAR in range, azimuth and elevation together with the ability of the radar to penetrate obscuring media. The approach is demonstrated using both simulated and real data from an automotive system.

Original languageEnglish
Pages (from-to)359-369
Number of pages11
JournalIET Radar, Sonar and Navigation
Volume15
Issue number4
Early online date2 Mar 2021
DOIs
Publication statusPublished - Apr 2021

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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