KMS of Xinjiang Astronomical Observatory, CAS
| Enhancing Mars Gravity Field Solutions with China's Tianwen-1 Tracking Data | |
| Sun, Shangbiao1; Yan, Jianguo1,2; Liu, Shanhong3,4; Wang, Chongyang1; Qiu, Denggao1; Barriot, Jean-Pierre1,5 | |
| 2025-02-01 | |
| Source Publication | ASTROPHYSICAL JOURNAL
 |
| ISSN | 0004-637X |
| Volume | 979Issue:2Pages:221 |
| Contribution Rank | 2 |
| Abstract | The Tianwen-1 (TW1) mission, which successfully entered Mars's orbit in 2021, provides a valuable data set for enhancing the understanding of Mars's gravity field. The highly elliptical near-polar orbit of the TW1 orbiter offers unique sensitivity to long-wavelength gravity signals, complementing the contributions of low-altitude missions like the Mars Reconnaissance Orbiter (MRO). In this study, we used 4 months of TW1 radio tracking data in combination with MRO data to develop a new Mars gravity field model up to degree and order 50. We evaluated the improvement of gravity field determination through power spectrum analysis, gravity anomaly maps, and trajectory precision assessment. The result shows significant improvements in accuracy up to degree and order 30, with an average enhancement of 38% in the zonal harmonic coefficients. There are obvious differences between the two gravity field models in gravity anomaly maps. The range of gravity anomaly errors improves after incorporating TW1 data, with the maximum error decreasing from 53.4 to 46.4 mGal and the average error improving from 8.4 to 7.3 mGal. Additionally, orbit determination experiments confirm that the fused gravity field model enhances trajectory modeling for both MRO and TW1. These findings highlight the scientific value of TW1 tracking data in advancing Mars's gravity field modeling and provide critical insights for future deep-space missions. |
| DOI | 10.3847/1538-4357/ada938 |
| Indexed By | SCI |
| Language | 英语 |
| WOS Keyword | SIGNALS ; MODEL ; MGS |
| Funding Project | National Natural Science Foundation of China[42241116] ; National Natural Science Foundation of China[42402230] ; National Key Research and Development Program of China[2022YFF0503202] ; The 2022 Project of Xinjiang Uygur Autonomous Regions of China for Heaven Lake Talent Program and Macau University of Science and Technology[SKL-LPS(MUST)-2021-2023] ; French Space Agency (CNES) |
| WOS Research Area | Astronomy & Astrophysics |
| WOS Subject | Astronomy & Astrophysics |
| WOS ID | WOS:001408905200001 |
| Publisher | IOP Publishing Ltd |
| Funding Organization | National Natural Science Foundation of China ; National Key Research and Development Program of China ; The 2022 Project of Xinjiang Uygur Autonomous Regions of China for Heaven Lake Talent Program and Macau University of Science and Technology ; French Space Agency (CNES) |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.xao.ac.cn/handle/45760611-7/7409 |
| Collection | 中国科学院新疆天文台 |
| Corresponding Author | Yan, Jianguo |
| Affiliation | 1.Wuhan Univ, State Key Lab Informat Engn Surveying, Mapping & Remote Sensing, Wuhan 430079, Peoples R China 2.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China 3.Beijing Aerosp Control Ctr, Beijing 100094, Peoples R China 4.Natl Key Lab Sci & Technol Aerosp Flight Dynam, Beijing 100094, Peoples R China 5.Univ French Polynesia, Geodesy Observ Tahiti, F-98702 Tahiti, France |
| Corresponding Author Affilication | Xinjiang Astronomical Observatory, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Sun, Shangbiao,Yan, Jianguo,Liu, Shanhong,et al. Enhancing Mars Gravity Field Solutions with China's Tianwen-1 Tracking Data[J]. ASTROPHYSICAL JOURNAL,2025,979(2):221. |
| APA | Sun, Shangbiao,Yan, Jianguo,Liu, Shanhong,Wang, Chongyang,Qiu, Denggao,&Barriot, Jean-Pierre.(2025).Enhancing Mars Gravity Field Solutions with China's Tianwen-1 Tracking Data.ASTROPHYSICAL JOURNAL,979(2),221. |
| MLA | Sun, Shangbiao,et al."Enhancing Mars Gravity Field Solutions with China's Tianwen-1 Tracking Data".ASTROPHYSICAL JOURNAL 979.2(2025):221. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Sun-2025-Enhancing M（1457KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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