PT  - JOURNAL ARTICLE
AU  - Gabela, Jelena
AU  - Kealy, Allison
AU  - Hedley, Mark
AU  - Moran, Bill
TI  - Case study of Bayesian RAIM algorithm integrated with Spatial Feature Constraint and Fault Detection and Exclusion algorithms for multi-sensor positioning
AID  - 10.1002/navi.433
DP  - 2021 Jun 20
TA  - NAVIGATION: Journal of the Institute of Navigation
PG  - 333--351
VI  - 68
IP  - 2
4099  - https://navi.ion.org/content/68/2/333.short
4100  - https://navi.ion.org/content/68/2/333.full
SO  - NAVIGATION2021 Jun 20; 68
AB  - This study proposes three novel integrity monitoring algorithms based on Bayesian Receiver Autonomous Integrity Monitoring (BRAIM). Two problems of integrity monitoring for land-based applications for GNSS challenging environments are explored: requirements for sufficient measurement redundancy and the presence of large biases. The need for measurement redundancy was mitigated by using BRAIM. This enabled the employment of a Fault Detection and Exclusion (FDE) algorithm without the required minimum availability of six measurements. To increase the estimated integrity, a Spatial Feature Constraint (SFC) algorithm was implemented to constrain solutions to feasible locations within a road feature. The performance of the proposed FDE+BRAIM, SFC+BRAIM and FDE+SFC+BRAIM algorithms was evaluated for GPS and multi-sensor data. For the non-Gaussian measurement error distribution and under the test conditions, the best achieved probability of misleading information was of the order of magnitude 10−8 for road-level requirements. The results provide an initial proof-of-concept for non-Gaussian non-linear multi-sensor integrity monitoring algorithms.