Considering measurement uncertainty in dynamic object tracking for autonomous driving applications-Reference-Cited by-同舟云学术

Considering measurement uncertainty in dynamic object tracking for autonomous driving applications

Published:2018-11-21 Issue:12 Volume:85 Page:764-778
ISSN:2196-7113
Container-title:tm - Technisches Messen
language:en
Short-container-title:

Author:

Naujoks Benjamin¹^ORCID,Engler Torsten¹,Michaelis Martin¹,Luettel Thorsten¹,Wuensche Hans-Joachim¹

Affiliation:

1. Institute for Autonomous Systems Technology , University of the Bundeswehr Munich , Werner-Heisenberg-Weg 39, 85579 Neubiberg , Germany

Abstract

Abstract Measurement uncertainty plays an important role in every real-world perception task. This paper describes the influence of measurement uncertainty in state estimation, which is the main part of Dynamic Object Tracking. Its base is the probabilistic Bayesian Filtering approach. Practical examples and tools for choosing the correct filter implementation including measurement models and their conversion, for different kinds of sensors are presented.

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering,Instrumentation

Link

https://www.degruyter.com/document/doi/10.1515/teme-2018-0018/pdf

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