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arXiv · 1907.04700

Cooperative Localization with Angular Measurements and Posterior Linearization

Yibo Wu·Bile Peng·Henk Wymeersch·Gonzalo Seco-Granados·Anastasios Kakkavas·Mario H. Castañeda Garcia·Richard A. Stirling-Gallacher
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Abstract

The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage. 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.

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Yibo Wu, Bile Peng, Henk Wymeersch, Gonzalo Seco-Granados, Anastasios Kakkavas, Mario H. Castañeda Garcia, Richard A. Stirling-Gallacher. 2019-07-10. Cooperative Localization with Angular Measurements and Posterior Linearization. https://arxiv.org/abs/1907.04700

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