Uncertainty Analysis of the Short-Arc Initial Orbit Determination
The solution of the short-arc angles-only orbit determination problem has large uncertainty because the topocentric range is not observable. For a certain angular observation tracklet with measurement noise, there exist numerous potential orbits, all of which are compatible with the observations. Ho...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8981969/ |
| _version_ | 1818917658186219520 |
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| author | Xuefeng Tao Zhi Li Qiuwu Gong Yasheng Zhang Ping Jiang |
| author_facet | Xuefeng Tao Zhi Li Qiuwu Gong Yasheng Zhang Ping Jiang |
| author_sort | Xuefeng Tao |
| collection | DOAJ |
| description | The solution of the short-arc angles-only orbit determination problem has large uncertainty because the topocentric range is not observable. For a certain angular observation tracklet with measurement noise, there exist numerous potential orbits, all of which are compatible with the observations. However, the solution of a deterministic initial orbit determination algorithm is usually far different from the true orbit, especially for the semimajor axis and the eccentricity. A new sampling method is proposed to describe the probability distribution of the orbit determination solutions. Firstly, a series of orbits are sampled in the semimajor axis - eccentricity plane. A chi-square test method is proposed to select candidate orbits from the sample orbits. The weights of the candidate orbits are calculated to measure their probability being the true orbit. Finally, the kernel density estimation algorithm is used to estimate the probability density function of the true orbits. With some a priori assumptions, the candidate orbits can be further screened, and their weight can be modified. The a priori knowledge can significantly improve the accuracy of the orbit determination solution. |
| first_indexed | 2024-12-20T00:37:34Z |
| format | Article |
| id | doaj.art-380b7a6e5a434b6c8eef87f1d9c288bb |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T00:37:34Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-380b7a6e5a434b6c8eef87f1d9c288bb2022-12-21T19:59:42ZengIEEEIEEE Access2169-35362020-01-018380453805910.1109/ACCESS.2020.29715888981969Uncertainty Analysis of the Short-Arc Initial Orbit DeterminationXuefeng Tao0https://orcid.org/0000-0001-8518-0546Zhi Li1https://orcid.org/0000-0003-0944-9886Qiuwu Gong2Yasheng Zhang3Ping Jiang4Department of Graduate Management, Space Engineering University, Beijing, ChinaDepartment of Aerospace Science and Technology, Space Engineering University, Beijing, ChinaJiuquan Satellite Launch Centre, Jiuquan, ChinaDepartment of Aerospace Science and Technology, Space Engineering University, Beijing, ChinaDepartment of Graduate Management, Space Engineering University, Beijing, ChinaThe solution of the short-arc angles-only orbit determination problem has large uncertainty because the topocentric range is not observable. For a certain angular observation tracklet with measurement noise, there exist numerous potential orbits, all of which are compatible with the observations. However, the solution of a deterministic initial orbit determination algorithm is usually far different from the true orbit, especially for the semimajor axis and the eccentricity. A new sampling method is proposed to describe the probability distribution of the orbit determination solutions. Firstly, a series of orbits are sampled in the semimajor axis - eccentricity plane. A chi-square test method is proposed to select candidate orbits from the sample orbits. The weights of the candidate orbits are calculated to measure their probability being the true orbit. Finally, the kernel density estimation algorithm is used to estimate the probability density function of the true orbits. With some a priori assumptions, the candidate orbits can be further screened, and their weight can be modified. The a priori knowledge can significantly improve the accuracy of the orbit determination solution.https://ieeexplore.ieee.org/document/8981969/Error analysisinitial orbit determinationKernel density estimationorbit samplingshort-arc optical observations |
| spellingShingle | Xuefeng Tao Zhi Li Qiuwu Gong Yasheng Zhang Ping Jiang Uncertainty Analysis of the Short-Arc Initial Orbit Determination IEEE Access Error analysis initial orbit determination Kernel density estimation orbit sampling short-arc optical observations |
| title | Uncertainty Analysis of the Short-Arc Initial Orbit Determination |
| title_full | Uncertainty Analysis of the Short-Arc Initial Orbit Determination |
| title_fullStr | Uncertainty Analysis of the Short-Arc Initial Orbit Determination |
| title_full_unstemmed | Uncertainty Analysis of the Short-Arc Initial Orbit Determination |
| title_short | Uncertainty Analysis of the Short-Arc Initial Orbit Determination |
| title_sort | uncertainty analysis of the short arc initial orbit determination |
| topic | Error analysis initial orbit determination Kernel density estimation orbit sampling short-arc optical observations |
| url | https://ieeexplore.ieee.org/document/8981969/ |
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