Bayesian Integrity Monitoring for Cellular Positioning - A Simplified Case Study
Paper in 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

Author

Liqin Ding

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Gonzalo Seco-Granados

Universitat Autonoma de Barcelona (UAB)

Hyowon Kim

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Russ Whiton

Volvo Cars

Erik Ström

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Jonas Sjöberg

Chalmers, Electrical Engineering, Systems and control

Henk Wymeersch

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

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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Areas of Advance

Information and Communication Technology

Subject Categories

Communication Systems

Computer Science

DOI

10.1109/ICCWorkshops57953.2023.10283608

More information

Latest update

3/28/2024