A belief propagation cooperative localization algorithm in GNSS-loss environments

Fei Ma; Guoping Tan; Siyuan Zhou; Hexuan Hu

doi:10.1117/12.2685589

28 July 2023 A belief propagation cooperative localization algorithm in GNSS-loss environments

Fei Ma, Guoping Tan, Siyuan Zhou, Hexuan Hu

Proceedings Volume 12716, Third International Conference on Digital Signal and Computer Communications (DSCC 2023); 1271606 (2023) https://doi.org/10.1117/12.2685589
Event: Third International Conference on Digital Signal and Computer Communications (DSCC 2023), 2023, Xi'an, China

Abstract

When vehicles are in driving environments such as urban roads and tunnels, the global navigation satellite system (GNSS) signal can fail to achieve positioning due to occlusion. Cooperative positioning can effectively improve the accuracy and coverage of vehicle positioning. In this paper, we address the vehicle localization issue in GNSS-Loss driving environments and with random packet loss due to wireless communications. We propose an improved cooperative localization algorithm based on belief propagation, which first linearizes the measurement model of distance by statistical linear regression method, then performs belief propagation based on the linearized model, and solves the packet loss problem by expanding the dimension of the vehicle state. From the simulation results, the algorithm can effectively reduce the impact of packet loss and improve the vehicle localization accuracy.

Citation Download Citation

Fei Ma, Guoping Tan, Siyuan Zhou, and Hexuan Hu "A belief propagation cooperative localization algorithm in GNSS-loss environments", Proc. SPIE 12716, Third International Conference on Digital Signal and Computer Communications (DSCC 2023), 1271606 (28 July 2023); https://doi.org/10.1117/12.2685589

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available