An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation
An improved UKF (Unscented Kalman Filter) algorithm is proposed to solve the problem of radar azimuth mutation. Since the radar azimuth angle will restart to count after each revolution of the radar, and when the aircraft just passes the abrupt angle change, the radar observation measurement will ha...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8863286 |
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| _version_ | 1832546915860873216 |
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| author | Dazhang You Pan Liu Wei Shang Yepeng Zhang Yawei Kang Jun Xiong |
| author_facet | Dazhang You Pan Liu Wei Shang Yepeng Zhang Yawei Kang Jun Xiong |
| author_sort | Dazhang You |
| collection | DOAJ |
| description | An improved UKF (Unscented Kalman Filter) algorithm is proposed to solve the problem of radar azimuth mutation. Since the radar azimuth angle will restart to count after each revolution of the radar, and when the aircraft just passes the abrupt angle change, the radar observation measurement will have a sudden change, which has serious consequences and is solved by the proposed novel UKF based on SVD. In order to improve the tracking accuracy and stability of the radar tracking system further, the SVD-MUKF (Singular Value Decomposition-based Memory Unscented Kalman Filter) based on multiple memory fading is constructed. Furthermore, several simulation results show that the SVD-MUKF algorithm proposed in this paper is better than the SVD-UKF (Singular Value Decomposition of Unscented Kalman Filter) algorithm and classical UKF algorithm in accuracy and stability. Last but not the least, the SVD-MUKF can achieve stable tracking of targets even in the case of angle mutation. |
| format | Article |
| id | doaj-art-f6a594d0203e47cca1748c5ad12932b0 |
| institution | Kabale University |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-f6a594d0203e47cca1748c5ad12932b02025-02-03T06:46:39ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742020-01-01202010.1155/2020/88632868863286An Improved Unscented Kalman Filter Algorithm for Radar Azimuth MutationDazhang You0Pan Liu1Wei Shang2Yepeng Zhang3Yawei Kang4Jun Xiong5School of Mechanical Engineering, Hubei University of Technology, Wuhan, ChinaSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, ChinaSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, ChinaSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, ChinaSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, ChinaSystem Design Institute of Hubei Aerospace Technology Academy, Wuhan, ChinaAn improved UKF (Unscented Kalman Filter) algorithm is proposed to solve the problem of radar azimuth mutation. Since the radar azimuth angle will restart to count after each revolution of the radar, and when the aircraft just passes the abrupt angle change, the radar observation measurement will have a sudden change, which has serious consequences and is solved by the proposed novel UKF based on SVD. In order to improve the tracking accuracy and stability of the radar tracking system further, the SVD-MUKF (Singular Value Decomposition-based Memory Unscented Kalman Filter) based on multiple memory fading is constructed. Furthermore, several simulation results show that the SVD-MUKF algorithm proposed in this paper is better than the SVD-UKF (Singular Value Decomposition of Unscented Kalman Filter) algorithm and classical UKF algorithm in accuracy and stability. Last but not the least, the SVD-MUKF can achieve stable tracking of targets even in the case of angle mutation.http://dx.doi.org/10.1155/2020/8863286 |
| spellingShingle | Dazhang You Pan Liu Wei Shang Yepeng Zhang Yawei Kang Jun Xiong An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation International Journal of Aerospace Engineering |
| title | An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation |
| title_full | An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation |
| title_fullStr | An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation |
| title_full_unstemmed | An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation |
| title_short | An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation |
| title_sort | improved unscented kalman filter algorithm for radar azimuth mutation |
| url | http://dx.doi.org/10.1155/2020/8863286 |
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