Bayesian Integrity Monitoring for Cellular Positioning — A Simplified Case Study
- Resource Type
- Conference
- Authors
- Ding, Liqin; Seco-Granados, Gonzalo; Kim, Hyowon; Whiton, Russ; Strom, Erik G.; Sjoberg, Jonas; Wymeersch, Henk
- Source
- 2023 IEEE International Conference on Communications Workshops (ICC Workshops) Communications Workshops (ICC Workshops), 2023 IEEE International Conference on. :1050-1056 May, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Three-dimensional displays
Message passing
Conferences
Estimation
Receivers
Numerical simulation
Inference algorithms
Cellular Positioning
Positioning Integrity
Bayesian Inference
Factor Graph
- Language
- ISSN
- 2694-2941
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 intearity risk (TIR) requirements.