{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:28:04Z","timestamp":1760236084277,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T00:00:00Z","timestamp":1635379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871012","62022012"],"award-info":[{"award-number":["61871012","62022012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFB0505602"],"award-info":[{"award-number":["2020YFB0505602"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Civil Aviation Security Capacity Building Fund Project","award":["CAAC Contract 2021(77)","CAAC Contract 2020(123)"],"award-info":[{"award-number":["CAAC Contract 2021(77)","CAAC Contract 2020(123)"]}]},{"name":"Beijing Nova Program of Science and Technology","award":["Z191100001119134"],"award-info":[{"award-number":["Z191100001119134"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An ionospheric anomaly is the irregular change of the ionosphere. It may result in potential threats for the ground-based augmentation system (GBAS) supporting the high-level precision approach. To counter the hazardous anomalies caused by the steep gradient in ionospheric delays, customized monitors are equipped in GBAS architectures. A major challenge is to rapidly detect the ionospheric gradient anomaly from environmental noise to meet the safety-critical requirements. A one-class support vector machine (OCSVM)-based monitor is developed to clearly detect ionospheric anomalies and to improve the robust detection speed. An offline-online framework based on the OCSVM is proposed to extract useful information related to anomalous characteristics in the presence of noise. To validate the effectiveness of the proposed framework, the influence of noise is fully considered and analyzed based on synthetic, semi-simulated, and real data from a typical ionospheric anomaly event. Synthetic results show that the OCSVM-based monitor can identify the anomaly that cannot be detected by other commonly-used monitors, such as the CCD-1OF, CCD-2OF and KLD-1OF. Semi-simulation results show that compared with other monitors, the newly proposed monitor can improve the average detection speed by more than 40% and decrease the minimum detectable gradient change rate to 0.002 m\/s. Furthermore, in the real ionospheric anomaly event experiment, compared with other monitors, the OCSVM-based monitor can improve the detection speed by 16%. The result indicates that the proposed monitor has encouraging potential to ensure integrity of the GBAS.<\/jats:p>","DOI":"10.3390\/rs13214327","type":"journal-article","created":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T23:52:35Z","timestamp":1635465155000},"page":"4327","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Ionospheric Anomaly Monitor Based on the One Class Support Vector Algorithm for the Ground-Based Augmentation System"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhen","family":"Gao","sequence":"first","affiliation":[{"name":"National Key Laboratory of CNS\/ATM, School of Electronics and Information Engineering, Beihang University, Beijing 100191, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4686-2354","authenticated-orcid":false,"given":"Kun","family":"Fang","sequence":"additional","affiliation":[{"name":"Research Institute for Frontier Science, Beihang University, Beijing 100191, China"}]},{"given":"Yanbo","family":"Zhu","sequence":"additional","affiliation":[{"name":"National Key Laboratory of CNS\/ATM, School of Electronics and Information Engineering, Beihang University, Beijing 100191, China"}]},{"given":"Zhipeng","family":"Wang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of CNS\/ATM, School of Electronics and Information Engineering, Beihang University, Beijing 100191, China"}]},{"given":"Kai","family":"Guo","sequence":"additional","affiliation":[{"name":"Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2RD, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,28]]},"reference":[{"key":"ref_1","unstructured":"Rife, J., Pullen, S., and Enge, P. 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