Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics
The large dynamic and high-speed flight of aerospace vehicle will bring unpredictable conditions to its navigation system, resulting in that its system random noise probability distribution will no longer meet the preconditions of Gaussian distribution preset by the existing filter algorithm, thus r...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2023/1897256 |
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| _version_ | 1832548025544736768 |
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| author | Jun Kang Zhi Xiong Rong Wang Xinrui Zhang |
| author_facet | Jun Kang Zhi Xiong Rong Wang Xinrui Zhang |
| author_sort | Jun Kang |
| collection | DOAJ |
| description | The large dynamic and high-speed flight of aerospace vehicle will bring unpredictable conditions to its navigation system, resulting in that its system random noise probability distribution will no longer meet the preconditions of Gaussian distribution preset by the existing filter algorithm, thus reducing the accuracy of the navigation system. So, it is very important to propose an effective method to solve the filter problem of the navigation system in non-Gaussian distribution to improve the accuracy of the navigation system. Therefore, an integrated navigation method of aerospace vehicle based on rank statistics (LRF) has been proposed in this paper. Firstly, based on the flight characteristics of aerospace vehicles, an accurate gravity calculation model has been established to improve the accuracy of system modelling. Then, the state equation and measurement equation of integrated navigation system have been established. In combination with the rank filter algorithm as well as the determined weights, sampling points are calculated and nonlinearly propagated through the transition matrix to achieve an accurate estimation about the predicted values of the state quantities and measurement quantities and the covariance matrix. In turn, it simulates the probability distribution of the system state effectively. Therefore, when the system random noise probability distribution of the aerospace vehicle does not meet the Gaussian distribution due to various interference factors in the actual flight process, the algorithm can simulate the probability distribution of the actual system to the greatest extent, to improve the accuracy of the integrated navigation system and enhance the reliability of the navigation system ultimately. |
| format | Article |
| id | doaj-art-eec80416de264763b7b278b1a81097ff |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-eec80416de264763b7b278b1a81097ff2025-02-03T06:42:38ZengWileyInternational Journal of Aerospace Engineering1687-59742023-01-01202310.1155/2023/1897256Integrated Navigation Method of Aerospace Vehicle Based on Rank StatisticsJun Kang0Zhi Xiong1Rong Wang2Xinrui Zhang3Navigation Research CentreNavigation Research CentreNavigation Research CentreNavigation Research CentreThe large dynamic and high-speed flight of aerospace vehicle will bring unpredictable conditions to its navigation system, resulting in that its system random noise probability distribution will no longer meet the preconditions of Gaussian distribution preset by the existing filter algorithm, thus reducing the accuracy of the navigation system. So, it is very important to propose an effective method to solve the filter problem of the navigation system in non-Gaussian distribution to improve the accuracy of the navigation system. Therefore, an integrated navigation method of aerospace vehicle based on rank statistics (LRF) has been proposed in this paper. Firstly, based on the flight characteristics of aerospace vehicles, an accurate gravity calculation model has been established to improve the accuracy of system modelling. Then, the state equation and measurement equation of integrated navigation system have been established. In combination with the rank filter algorithm as well as the determined weights, sampling points are calculated and nonlinearly propagated through the transition matrix to achieve an accurate estimation about the predicted values of the state quantities and measurement quantities and the covariance matrix. In turn, it simulates the probability distribution of the system state effectively. Therefore, when the system random noise probability distribution of the aerospace vehicle does not meet the Gaussian distribution due to various interference factors in the actual flight process, the algorithm can simulate the probability distribution of the actual system to the greatest extent, to improve the accuracy of the integrated navigation system and enhance the reliability of the navigation system ultimately.http://dx.doi.org/10.1155/2023/1897256 |
| spellingShingle | Jun Kang Zhi Xiong Rong Wang Xinrui Zhang Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics International Journal of Aerospace Engineering |
| title | Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics |
| title_full | Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics |
| title_fullStr | Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics |
| title_full_unstemmed | Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics |
| title_short | Integrated Navigation Method of Aerospace Vehicle Based on Rank Statistics |
| title_sort | integrated navigation method of aerospace vehicle based on rank statistics |
| url | http://dx.doi.org/10.1155/2023/1897256 |
| work_keys_str_mv | AT junkang integratednavigationmethodofaerospacevehiclebasedonrankstatistics AT zhixiong integratednavigationmethodofaerospacevehiclebasedonrankstatistics AT rongwang integratednavigationmethodofaerospacevehiclebasedonrankstatistics AT xinruizhang integratednavigationmethodofaerospacevehiclebasedonrankstatistics |