Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles
Stellar refraction autonomous navigation provides a promising alternative for cross-domain vehicles, particularly in near-space environments where traditional inertial and satellite navigation methods face limitations. This study develops a stellar refraction navigation system that utilizes stellar...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/14/2367 |
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| author | Yuchang Xu Yang Zhang Xiaokang Wang Guanbing Zhang Guang Yang Hong Yuan |
| author_facet | Yuchang Xu Yang Zhang Xiaokang Wang Guanbing Zhang Guang Yang Hong Yuan |
| author_sort | Yuchang Xu |
| collection | DOAJ |
| description | Stellar refraction autonomous navigation provides a promising alternative for cross-domain vehicles, particularly in near-space environments where traditional inertial and satellite navigation methods face limitations. This study develops a stellar refraction navigation system that utilizes stellar refraction angle observations and the Implicit Unscented Kalman Filter (IUKF) for state estimation. A representative orbit with altitudes ranging from 60 km to 200 km is designed to simulate cross-domain flight conditions. The navigation performance is analyzed under varying conditions, including orbital altitude, as well as star sensor design parameters, such as limiting magnitude, field of view (FOV) value, and measurement error, along with different sampling intervals. The simulation results show that increasing the limiting magnitude from 5 to 8 reduced the position error from 705.19 m to below 1 m, with optimal accuracy reaching 0.89 m when using a 20° × 20° field of view and a 3 s sampling interval. In addition, shorter sampling intervals improved accuracy and filter stability, while longer intervals introduced greater integration drift. When the sampling interval reached 100 s, position error grew to the kilometer level. These findings validate the feasibility of using stellar refraction for autonomous navigation in cross-domain scenarios and provide design guidance for optimizing star sensor configurations and sampling strategies in future near-space navigation systems. |
| format | Article |
| id | doaj-art-8d3dec5d48c34e35beb8f2e454747d1d |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-8d3dec5d48c34e35beb8f2e454747d1d2025-08-20T03:32:27ZengMDPI AGRemote Sensing2072-42922025-07-011714236710.3390/rs17142367Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain VehiclesYuchang Xu0Yang Zhang1Xiaokang Wang2Guanbing Zhang3Guang Yang4Hong Yuan5Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaStellar refraction autonomous navigation provides a promising alternative for cross-domain vehicles, particularly in near-space environments where traditional inertial and satellite navigation methods face limitations. This study develops a stellar refraction navigation system that utilizes stellar refraction angle observations and the Implicit Unscented Kalman Filter (IUKF) for state estimation. A representative orbit with altitudes ranging from 60 km to 200 km is designed to simulate cross-domain flight conditions. The navigation performance is analyzed under varying conditions, including orbital altitude, as well as star sensor design parameters, such as limiting magnitude, field of view (FOV) value, and measurement error, along with different sampling intervals. The simulation results show that increasing the limiting magnitude from 5 to 8 reduced the position error from 705.19 m to below 1 m, with optimal accuracy reaching 0.89 m when using a 20° × 20° field of view and a 3 s sampling interval. In addition, shorter sampling intervals improved accuracy and filter stability, while longer intervals introduced greater integration drift. When the sampling interval reached 100 s, position error grew to the kilometer level. These findings validate the feasibility of using stellar refraction for autonomous navigation in cross-domain scenarios and provide design guidance for optimizing star sensor configurations and sampling strategies in future near-space navigation systems.https://www.mdpi.com/2072-4292/17/14/2367cross-domain navigationstellar refraction navigationUnscented Kalman Filterstar sensor |
| spellingShingle | Yuchang Xu Yang Zhang Xiaokang Wang Guanbing Zhang Guang Yang Hong Yuan Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles Remote Sensing cross-domain navigation stellar refraction navigation Unscented Kalman Filter star sensor |
| title | Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles |
| title_full | Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles |
| title_fullStr | Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles |
| title_full_unstemmed | Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles |
| title_short | Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles |
| title_sort | performance analysis of stellar refraction autonomous navigation for cross domain vehicles |
| topic | cross-domain navigation stellar refraction navigation Unscented Kalman Filter star sensor |
| url | https://www.mdpi.com/2072-4292/17/14/2367 |
| work_keys_str_mv | AT yuchangxu performanceanalysisofstellarrefractionautonomousnavigationforcrossdomainvehicles AT yangzhang performanceanalysisofstellarrefractionautonomousnavigationforcrossdomainvehicles AT xiaokangwang performanceanalysisofstellarrefractionautonomousnavigationforcrossdomainvehicles AT guanbingzhang performanceanalysisofstellarrefractionautonomousnavigationforcrossdomainvehicles AT guangyang performanceanalysisofstellarrefractionautonomousnavigationforcrossdomainvehicles AT hongyuan performanceanalysisofstellarrefractionautonomousnavigationforcrossdomainvehicles |