Optimization and Processing of Helicopter Axis Trajectory Measurement Data
In order to improve the validity of the measured data of the axis trajectory, a data optimization algorithm combining multiple algorithms is proposed in this paper. Firstly, the box graph theory is used to detect the abnormal data, and then the use of median filter is improved. For the abnormal valu...
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Published in | 2022 IEEE International Conference on Unmanned Systems (ICUS) pp. 670 - 675 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
28.10.2022
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Abstract | In order to improve the validity of the measured data of the axis trajectory, a data optimization algorithm combining multiple algorithms is proposed in this paper. Firstly, the box graph theory is used to detect the abnormal data, and then the use of median filter is improved. For the abnormal values detected, the improved strong tracking filter algorithm is inserted into the Kalman smoothing algorithm to realize the data optimization. At the same time, a strong tracking sequential fusion algorithm is used to realize the data fusion. Finally, through the algorithm to optimize the real axis trajectory measurement data, it is found that the algorithm can accurately detect and eliminate abnormal values, and can also smooth and optimize the data to achieve effective data fusion and improve the authenticity of the data. |
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AbstractList | In order to improve the validity of the measured data of the axis trajectory, a data optimization algorithm combining multiple algorithms is proposed in this paper. Firstly, the box graph theory is used to detect the abnormal data, and then the use of median filter is improved. For the abnormal values detected, the improved strong tracking filter algorithm is inserted into the Kalman smoothing algorithm to realize the data optimization. At the same time, a strong tracking sequential fusion algorithm is used to realize the data fusion. Finally, through the algorithm to optimize the real axis trajectory measurement data, it is found that the algorithm can accurately detect and eliminate abnormal values, and can also smooth and optimize the data to achieve effective data fusion and improve the authenticity of the data. |
Author | Ge, Quanbo He, Hongli Wang, Yuanliang |
Author_xml | – sequence: 1 givenname: Hongli surname: He fullname: He, Hongli email: 343137051@qq.com organization: Chinese Flight Test Establishment,Xian,China – sequence: 2 givenname: Yuanliang surname: Wang fullname: Wang, Yuanliang email: 501319531@qq.com organization: Shanghai Maritime University,Shanghai,China – sequence: 3 givenname: Quanbo surname: Ge fullname: Ge, Quanbo email: QuanboGe@163.com organization: Nanjing University of Information Science & Technology,Nanjing,China |
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Snippet | In order to improve the validity of the measured data of the axis trajectory, a data optimization algorithm combining multiple algorithms is proposed in this... |
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SubjectTerms | axis trajectory box graph theory Data integration Filtering algorithms Filtering theory Graph theory Helicopters kalman smoothing median filtering sequential fusion Smoothing methods Trajectory |
Title | Optimization and Processing of Helicopter Axis Trajectory Measurement Data |
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