Solar Synchronous Orbits. Predicting the Mean Local Time of the Ascending Node

Andrey Nazarenko

Solar Synchronous Orbits. Predicting the Mean Local Time of the Ascending Node

Andrey Nazarenko *

Contact

Solar Synchronous Orbits. Predicting the Mean Local Time of the Ascending Node

Article Fingerprint

ReserarchID

REAUYZE

Solar Synchronous Orbits. Predicting the Mean Local Time of the Ascending Node Banner

Key Research Insights

Synthesized scholarly intelligence & interactive research assistant

This converted HTML version may contain rendering inconsistencies. Please refer to the PDF for the authoritative version, or click here to provide feedback.

Abstract

Based on the orbital data of the Meteor M1 spacecraft, the possible causes of the deviations of the mean local time of the ascending node (MLTAN) from the initial value are considered. It has been established that the main cause of deviations is the change in inclination. This occurs as a result of solar gravitational disturbances and leads to a change in the MLTAN under the law, which at intervals of up to 7 years is close to parabola. In general, these variations are long-period with the period of 28 years. The simplified system of differential equations describing the evolution of inclination and MLTAN has been proposed. The results of the integration of this system of equations are well consistent with the real data on the evolution of the parameters of the orbit of the Meteor M1 spacecraft.

References

8 Cites in Article

Reference Format

1. Jeffrey Kroessler (2020). New York, Year by Year. Year
2. Д Виноградов,Е Давыдов (2016). Techniques of shaping steady near-circular solar-synchronous orbits for the long term existence of the spacecraft. Engineering Journal: Science and Innovation
3. I Balashov,М Burtsev,А Burtsev,A Matveev,А Mazurov,K Senko (2010). Usage of MODIS and VIIRS Combined Data for Forest Fires Area Estimation Experience. Information Technologies in Remote Sensing of the Earth - RORSE 2018, 164-170.
4. В Юрасов,Астросовет (1987). Применение универсального численно-аналитического метода для прогнозирования движения спутников в атмосфере. Труды совещания «Проблемы физики верхней атмосферы и динамики искусственных спутников Земли. проведенного в г. Ужгород 25-28 июня 1985 года
5. В Юрасов,Т Амелина (1994). А. Применение универсального численноаналитического метода для прогнозирования движения геостационарных спутников. конференции «Программы наблюдения спутников и небесных тел солнечной системы. А. Применение универсального численноаналитического метода для прогнозирования движения геостационарных спутников. конференции «Программы наблюдения спутников и небесных тел солнечной системы
6. V Yurasov (1996). Universal Semianalytic Satellite Motion Propagation Method. Proceedings of the Second U.S.-Russian Space Surveillance Workshop
7. Благодарность (2009). Благодарность. Благодарность
8. В С Автор Признателен К.Т.Н,Юрасову (2021). Анализ полученных результатов. Практическое пособие по сезонной корректировке программным обеспечением JDemetra+, 51-80.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Andrey Nazarenko. 2020. "Solar Synchronous Orbits. Predicting the Mean Local Time of the Ascending Node". Global Journal of Research in Engineering - I: Numerical Methods GJRE-I Volume 20 (GJRE Volume 20 Issue I1).

More Citation Formats

Select Citation Style:

Download Citation

GJRE Volume 20 Issue I1

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

Not Found

Classification

GJRE-I Classification FOR Code: 230116

Submission ReceivedDecember 9, 2019
Peer Review Double Blind
Handling Editor
Accepted December 31, 2019
Published January 15, 2020

Version of record

v1.2

Issue date

July 3, 2020

Language

Russian

Order Article Reprint

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Views: 936

Total Downloads: 42

All Trends