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

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

Conference Paper (2017)

Author(s)

Joris Domhof (TU Delft - Mechanical Engineering)

Riender Happee (TU Delft - Mechanical Engineering)

Pieter Jonker (TU Delft - Mechanical Engineering)

Research Group

Intelligent Vehicles

Measurement uncertainty Cameras Radar tracking Automobiles Laser radar Covariance matrices

DOI related publication

https://doi.org/10.23919/ICIF.2017.8009637 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:41539917-2baf-485d-bac4-aed0a9dc2613

More Info

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Publication Year

2017

Language

English

Research Group

Intelligent Vehicles

ISBN (print)

978-0-9964-5270-0

Event

20th International Conference on Information Fusion (2017-07-10 - 2017-07-13), Xi'an, China

Downloads counter

206

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.