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

Conference paper (2017)

Authors

J.F.M. Domhof Intelligent Vehicles - Mechanical, Maritime and Materials Engineering
R Happee Intelligent Vehicles - Mechanical, Maritime and Materials Engineering
P.P. Jonker Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
Research Group
Intelligent Vehicles (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2017

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Intelligent Vehicles

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.

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