Online Targetless Radar-Camera Extrinsic Calibration Based on the Common Features of Radar and Camera

Lei Cheng, Siyang Cao

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

Abstract

Sensor fusion is essential for autonomous driving and autonomous robots, and radar-camera fusion systems have gained popularity due to their complementary sensing capabilities. However, accurate calibration between these two sensors is crucial to ensure effective fusion and improve overall system performance. Calibration involves intrinsic and extrinsic calibration, with the latter being particularly important for achieving accurate sensor fusion. Unfortunately, many target-based calibration methods require complex operating procedures and well-designed experimental conditions, posing challenges for researchers attempting to reproduce the results. To address this issue, we introduce a novel approach that leverages deep learning to extract a common feature from raw radar data (i.e., Range-Doppler-Angle data) and camera images. Instead of explicitly representing these common features, our method implicitly utilizes these common features to match identical objects from both data sources. Specifically, the extracted common feature serves as an example to demonstrate an online targetless calibration method between the radar and camera systems. The estimation of the extrinsic transformation matrix is achieved through this feature-based approach. To enhance the accuracy and robustness of the calibration, we apply the RANSAC and Levenberg-Marquardt (LM) nonlinear optimization algorithm for deriving the matrix. Our experiments in the real world demonstrate the effectiveness and accuracy of our proposed method.

Original languageEnglish (US)
Title of host publicationNAECON 2023 - IEEE National Aerospace and Electronics Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages294-299
Number of pages6
ISBN (Electronic)9798350338782
DOIs
StatePublished - 2023
Externally publishedYes
Event2023 IEEE National Aerospace and Electronics Conference, NAECON 2023 - Dayton, United States
Duration: Aug 28 2023Aug 31 2023

Publication series

NameProceedings of the IEEE National Aerospace Electronics Conference, NAECON
ISSN (Print)0547-3578
ISSN (Electronic)2379-2027

Conference

Conference2023 IEEE National Aerospace and Electronics Conference, NAECON 2023
Country/TerritoryUnited States
CityDayton
Period8/28/238/31/23

Keywords

  • common features
  • extrinsic calibration
  • radar
  • radar-camera calibration
  • sensor fusion

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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