Vehicle positioning system with multi‐hypothesis map matching and robust feedback-Reference-Cited by-同舟云学术

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Vehicle positioning system with multi‐hypothesis map matching and robust feedback

Published:2017-07-21 Issue:10 Volume:11 Page:649-658
ISSN:1751-9578
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET Intelligent Transport Systems

Author:

Zhang Kai¹²,Liu Shaojun²,Dong Yuhan¹²^ORCID,Wang Daoshun³,Zhang Yi¹²⁴,Miao Lixin¹²

Affiliation:

1. Graduate School at ShenzhenTsinghua UniversityShenzhenPeople's Republic of China

2. Tsinghua‐Berkeley Shenzhen InstituteShenzhenPeople's Republic of China

3. Department of Computer Science and TechnologyTsinghua UniversityBeijingPeople's Republic of China

4. Department of AutomationTsinghua National Laboratory for Information Science and TechnologyTsinghua UniversityBeijingPeople's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2017.0072

Reference27 articles.

1. Global positioning systems in the time domain: how useful a tool for intelligent vehicle‐highway systems;Zito R.;Transp. Res. C: Emerging Technol.,1995

2. GPS/IMU data fusion using multisensor Kalman filtering: introduction of contextual aspects

3. An extended Kalman filter algorithm for integrating GPS and low cost dead reckoning system data for vehicle performance and emissions monitoring;Zhao L.;J. Navig.,2003

4. SasiadekJ.Z.WangQ.ZerembaM.B.: ‘Fuzzy adaptive Kalman filtering for INS/GPS data fusion’.Proc. of the 2000 IEEE Int. Symp. on IEEE 2000 pp.181–186

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