Multi-sensor object tracking performance limits by the Cramer-Rao lower bound

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

This paper presents a systematic approach to evaluate the tracking performance limits for different sensor modalities (lidar, radar and vision) and for combination of these sensors modalities. The Cramer-Rao lower bound (CRLB) is used to predict the tracking performance limits for state of the art sensors such as the Continental ARS408 radar, Velodyne HDL-64E lidar and a state of the art monocular/stereo camera. The performance is evaluated by computing the theoretical CRLB in urban and highway environments. In both scenarios, the best performance was achieved by a combination of lidar and radar. In the close range, stereo vision improves the longitudinal tracking performance limits. Furthermore, radar is crucial on highways because of the quick longitudinal convergence characteristics.
Original languageEnglish
Title of host publicationProceedings of the 20th International Conference on Information Fusion
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Number of pages8
ISBN (Print)978-0-9964-5270-0
DOIs
Publication statusPublished - 2017
Event20th International Conference on Information Fusion - Xi'an, China
Duration: 10 Jul 201713 Jul 2017

Conference

Conference20th International Conference on Information Fusion
CountryChina
CityXi'an
Period10/07/1713/07/17

Keywords

  • Radar tracking
  • Laser radar
  • Covariance matrices
  • Cameras
  • Automobiles
  • Measurement uncertainty

Fingerprint

Dive into the research topics of 'Multi-sensor object tracking performance limits by the Cramer-Rao lower bound'. Together they form a unique fingerprint.

Cite this