Zhu, Songyan und Li, Xiaoying und Xu, Jian und Cheng, Tianhai und Zhang, Xingying und Wang, Hongmei und Wang, Yapeng und Miao, Jing (2019) Neural network aided fast pointing information determination approach for occultation payloads from in-flight measurements: Algorithm design and assessment. Advances in Space Research, 63 (8), Seiten 2323-2336. Elsevier. doi: 10.1016/j.asr.2019.01.041. ISSN 0273-1177.
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Offizielle URL: https://www.sciencedirect.com/science/article/pii/S0273117719300766
Kurzfassung
Pointing information is decisive to solving precise profile retrieval issues from occultation measurements. Research regarding tratospheric O3 hole in Antarctic and surface O3 pollution would significantly benefit from massive occultation measurements. A neural network aided pointing information determination approach, in terms of tangent heights, is proposed to address issues requiring fast and easy-to-use determined tangent heights. The geometrical triangular iteration (GTI) algorithm in this work is based on N2 absorption microwindows, and several treatments (e.g., tangential stride generator and triangular-net optimization) are adopted. In addition, LSTM is employed to reduce time consumption and increase accuracy. Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) in-flight measurements are used to assess this approach. The comparison between the proposed algorithm and eight official products indicates a promising performance. Correlation coefficient for each orbit is greater than 0.99. The processing time is about 16.6 min per orbit with an average cost of 0.06. The introduction of LSTM technique demonstrates an approximate 28.49% better result, with less computation time. It costed less than 30 s to determine eight orbit tangent heights. In general, although minor issues remain, this LSTM-aided GTI algorithm is applicable in industry.
elib-URL des Eintrags: | https://elib.dlr.de/126832/ | ||||||||||||||||||||||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||||||||||||||||||
Titel: | Neural network aided fast pointing information determination approach for occultation payloads from in-flight measurements: Algorithm design and assessment | ||||||||||||||||||||||||||||||||||||
Autoren: |
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Datum: | April 2019 | ||||||||||||||||||||||||||||||||||||
Erschienen in: | Advances in Space Research | ||||||||||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||||||||||||||
Band: | 63 | ||||||||||||||||||||||||||||||||||||
DOI: | 10.1016/j.asr.2019.01.041 | ||||||||||||||||||||||||||||||||||||
Seitenbereich: | Seiten 2323-2336 | ||||||||||||||||||||||||||||||||||||
Herausgeber: |
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Verlag: | Elsevier | ||||||||||||||||||||||||||||||||||||
ISSN: | 0273-1177 | ||||||||||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||||||||||
Stichwörter: | Occultation observation, Pointing information, N2 absorption, Tangential strides, Triangular iteration, LSTM | ||||||||||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Fernerkundung u. Geoforschung | ||||||||||||||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > Atmosphärenprozessoren | ||||||||||||||||||||||||||||||||||||
Hinterlegt von: | Xu, Dr.-Ing. Jian | ||||||||||||||||||||||||||||||||||||
Hinterlegt am: | 15 Mär 2019 13:13 | ||||||||||||||||||||||||||||||||||||
Letzte Änderung: | 01 Mai 2020 03:00 |
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