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.

Angle measurement

Linearization

Mean square error

Vehicles

Författare

Yibo Wu

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Bile Peng

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

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,

Ämneskategorier

Kommunikationssystem

Reglerteknik

Signalbehandling

DOI

10.1109/ICCWorkshops49005.2020.9145275

Mer information

Senast uppdaterat

2020-09-28