Cooperative localization with angular measurements and posterior linearization
Paper i proceeding, 2020

The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage of the positioning. Conventional distance measurements between vehicles are limited by the need for synchronization and provide no heading information of the vehicle. To address this, we present a cooperative localization algorithm using posterior linearization belief propagation (PLBP) utilizing angle-of-arrival (AoA)-only measurements. Simulation results show that both directional and positional root mean squared error (RMSE) of vehicles can be decreased significantly and converge to a low value in a few iterations. Furthermore, the influence of parameters for the vehicular network, such as vehicle density, communication radius, prior uncertainty, and AoA measurements noise, is analyzed.

Vehicles

Linearization

Mean square error

Angle measurement

Författare

Yibo Wu

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Bile Peng

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

G. Seco-Granados

Universitat Autonoma de Barcelona (UAB)

Anastasios Kakkavas

Technische Universität München

Mario H.Castaneda Garcia

Technische Universität München

Richard A. Stirling-Gallacher

Technische Universität München

2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings

9145275

2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020
Dublin, Ireland,

Fifth Generation Communication Automotive Research and innovation (5GCAR)

Europeiska kommissionen (EU) (EC/H2020/761510), 2017-06-01 -- 2019-05-31.

Ämneskategorier

Kommunikationssystem

Reglerteknik

Signalbehandling

DOI

10.1109/ICCWorkshops49005.2020.9145275

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Senast uppdaterat

2024-01-03