Bayesian Integrity Monitoring for Cellular Positioning - A Simplified Case Study
Paper i proceeding, 2023

Bayesian receiver autonomous integrity monitoring (RAIM) algorithms are developed for the snapshot cellular positioning problem in a simplified one-dimensional (1D) linear Gaussian setting. They allow for position estimation, multi-fault detection and exclusion, and protection level (PL) computation by the efficient and exact computation of the position posterior probabilities via message passing along a factor graph. Numerical simulations show that the proposed Bayesian RAIM algorithms achieve significant performance improvement over a baseline advanced RAIM algorithm by providing tighter protection levels (PLs) that meet the target integrity risk (TIR) requirements.

Positioning Integrity

Bayesian Inference

Cellular Positioning

Factor Graph

Författare

Liqin Ding

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Gonzalo Seco-Granados

Universitat Autonoma de Barcelona (UAB)

Hyowon Kim

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Russ Whiton

Volvo Cars

Erik Ström

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Jonas Sjöberg

Chalmers, Elektroteknik, System- och reglerteknik

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

2023 IEEE International Conference on Communications Workshops, ICC Workshops 2023

1050-1056
9798350333077 (ISBN)

2023 IEEE International Conference on Communications Workshops, ICC Workshops 2023
Rome, Italy,

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Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Kommunikationssystem

Datavetenskap (datalogi)

DOI

10.1109/ICCWorkshops57953.2023.10283608

Mer information

Senast uppdaterat

2024-03-28