Abstract: | Faulty signals from global navigation satellite systems (GNSSs) often lead to erroneous position estimates. A variety of fault detection and exclusion (FDE) methods have been proposed in prior research to both detect and exclude faulty measurements. This paper introduces a new technique for the FDE of GNSS measurements using Euclidean distance matrices. After a brief introduction to Euclidean distance matrices, both the detection and exclusion strategy is explained in detail. Euclidean distance matrix-based FDE is verified in two separate real-world data sets and proven to accurately detect and exclude GNSS faults on an average of 1.4-times faster than residual-based FDE and 70-times faster than solution separation FDE. |
Video Abstract: | |
Published in: | NAVIGATION: Journal of the Institute of Navigation, Volume 70, Number 1 |
Cite this article: |
Citation Tools
https://doi.org/10.33012/navi.555 |
Full Paper: |
ION Members: Free Download Non-Members: Free Download Sign In |