Journal
APPLIED SCIENCES-BASEL
Volume 11, Issue 21, Pages -Publisher
MDPI
DOI: 10.3390/app112110181
Keywords
two-line elements; simplified perturbation models; Keplarian elements; trial & error and maneuver detection
Categories
Funding
- Ministry of Science and Technology, The Republic of China [MOST 108-2823-8-194-002, 109-2622-8-194-001-TE1, 109-2622-8-194-007]
- Advanced Institute of Manufacturing with High-tech Innovations
- Center for Innovative Research on Aging Society from The Featured Areas Research Center Program
- Ministry of Education in Taiwan
Ask authors/readers for more resources
An algorithm for identifying satellite maneuvers was developed in this study by comparing Keplerian elements from TLEs and simplified perturbation models. The effectiveness of the method was evaluated in case studies involving TOPEX/Poseidon and Envisat, demonstrating the ability to detect maneuvers even with small magnitudes when detection parameters are properly calibrated.
In this study, an algorithm to identify the maneuvers of a satellite is developed by comparing the Keplerian elements acquired from the two-line elements (TLEs) and Keplerian elements propagated from simplified perturbation models. TLEs contain a specific set of orbital elements, whereas the simplified perturbation models are used to propagate the state vectors at a given time. By comparing the corresponding Keplerian elements derived from both methods, a satellite's maneuver is identified. This article provides an outline of the working methodology and efficacy of the method. The function of this approach is evaluated in two case studies, i.e., TOPEX/Poseidon and Envisat, whose maneuver histories are available. The same method is implemented to identify the station-keeping maneuvers for TDRS-3, whose maneuver history is not available. Results derived from the analysis indicate that maneuvers with a magnitude of even as low as cm/s are detected when the detection parameters are calibrated properly.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available