Cooperative localization with angular measurements and posterior linearization
Paper in proceedings, 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.

Linearization

Angle measurement

Vehicles

Mean square error

Author

Yibo Wu

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Bile Peng

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Henk Wymeersch

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

G. Seco-Granados

Universitat Autonoma de Barcelona (UAB)

Anastasios Kakkavas

Technical University of Munich

Mario H.Castaneda Garcia

Technical University of Munich

Richard A. Stirling-Gallacher

Technical University of Munich

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)

European Commission (EC), 2017-06-01 -- 2019-05-31.

Subject Categories

Communication Systems

Control Engineering

Signal Processing

DOI

10.1109/ICCWorkshops49005.2020.9145275

More information

Latest update

2/11/2021