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https://doi.org/10.21256/zhaw-21744| Publication type: | Article in scientific journal |
| Type of review: | Peer review (publication) |
| Title: | Network‐based ionospheric gradient monitoring to support GBAS |
| Authors: | Caamano, Maria Juan, José Miguel Felux, Michael Gerbeth, Daniel González‐Casado, Guillermo Sanz, Jaume |
| et. al: | No |
| DOI: | 10.1002/navi.411 10.21256/zhaw-21744 |
| Published in: | Navigation : Journal of the Institute of Navigation |
| Volume(Issue): | 68 |
| Issue: | 1 |
| Page(s): | 135 |
| Pages to: | 156 |
| Issue Date: | 11-Feb-2021 |
| Publisher / Ed. Institution: | Wiley |
| ISSN: | 0028-1522 2161-4296 |
| Language: | English |
| Subjects: | GNSS; Ionosphere; GBAS |
| Subject (DDC): | 629: Aeronautical, automotive engineering |
| Abstract: | Large ionospheric gradients acting between a Ground Based Augmentation System (GBAS) reference station and an aircraft on approach could lead to hazardous position errors if undetected. Current GBAS stations provide solutions against this threat that rely on the use of “worst‐case” conservative threat models, which could limit the availability of the system. This paper presents a methodology capable of detecting ionospheric gradients in real time and estimating the actual threat model parameters based on a network of dual‐frequency and multi‐constellation GNSS monitoring stations. First, we evaluate the performance of our algorithm with synthetic gradients that are simulated over the nominal measurements recorded by a reference network in Alaska. Afterwards, we also assess it with one real ionospheric gradient measured by the same network. Results with both simulated gradients and a real gradient show the potential to support GBAS by detecting and estimating these gradients instead of always using “worst‐case” models. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/21744 |
| Fulltext version: | Published version |
| License (according to publishing contract): | CC BY 4.0: Attribution 4.0 International |
| Departement: | School of Engineering |
| Organisational Unit: | Centre for Aviation (ZAV) |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2021_Caamano_etal_Network‐based-ionospheric-gradient-monitoring-to-support-GBAS.pdf | 2.79 MB | Adobe PDF |  View/Open |
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Caamano, M., Juan, J. M., Felux, M., Gerbeth, D., González‐Casado, G., & Sanz, J. (2021). Network‐based ionospheric gradient monitoring to support GBAS. Navigation : Journal of the Institute of Navigation, 68(1), 135–156. https://doi.org/10.1002/navi.411
Caamano, M. et al. (2021) ‘Network‐based ionospheric gradient monitoring to support GBAS’, Navigation : Journal of the Institute of Navigation, 68(1), pp. 135–156. Available at: https://doi.org/10.1002/navi.411.
M. Caamano, J. M. Juan, M. Felux, D. Gerbeth, G. González‐Casado, and J. Sanz, “Network‐based ionospheric gradient monitoring to support GBAS,” Navigation : Journal of the Institute of Navigation, vol. 68, no. 1, pp. 135–156, Feb. 2021, doi: 10.1002/navi.411.
CAAMANO, Maria, José Miguel JUAN, Michael FELUX, Daniel GERBETH, Guillermo GONZÁLEZ‐CASADO und Jaume SANZ, 2021. Network‐based ionospheric gradient monitoring to support GBAS. Navigation : Journal of the Institute of Navigation. 11 Februar 2021. Bd. 68, Nr. 1, S. 135–156. DOI 10.1002/navi.411
Caamano, Maria, José Miguel Juan, Michael Felux, Daniel Gerbeth, Guillermo González‐Casado, and Jaume Sanz. 2021. “Network‐Based Ionospheric Gradient Monitoring to Support GBAS.” Navigation : Journal of the Institute of Navigation 68 (1): 135–56. https://doi.org/10.1002/navi.411.
Caamano, Maria, et al. “Network‐Based Ionospheric Gradient Monitoring to Support GBAS.” Navigation : Journal of the Institute of Navigation, vol. 68, no. 1, Feb. 2021, pp. 135–56, https://doi.org/10.1002/navi.411.
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