One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking
The approach of tracking maneuvering targets based on the “Current” Statistical (CS) model is widely used. The method needs to preset maneuvering frequency and maximum acceleration based on experience. In practice, the preset values are often not consistent with the actual moving state of targets an...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
China Science Publishing & Media Ltd. (CSPM)
2013-06-01
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| Series: | Leida xuebao |
| Subjects: | |
| Online Access: | http://radars.ie.ac.cn/EN/abstract/abstract85.shtml# |
| _version_ | 1797428703343411200 |
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| author | Qian Guang-hua Li Ying Luo Rong-jian |
| author_facet | Qian Guang-hua Li Ying Luo Rong-jian |
| author_sort | Qian Guang-hua |
| collection | DOAJ |
| description | The approach of tracking maneuvering targets based on the “Current” Statistical (CS) model is widely used. The method needs to preset maneuvering frequency and maximum acceleration based on experience. In practice, the preset values are often not consistent with the actual moving state of targets and result in larger tracking errors. In order to tackle the problem, this paper initially deduces a self-adapting maneuvering frequency algorithm from the discrete state equation of the CS model. Then, an improved self-adapting acceleration covariance algorithm is presented. Simulation results show that, by using the self-adapting maneuvering frequency algorithm and the improved self-adapting acceleration covariance algorithm to track targets simultaneously, the ability to self-adapt to the fluctuation of the moving state will be improved. The tracking accuracy is also improved, and the convergence speed of the algorithm is quicker. |
| first_indexed | 2024-03-09T09:02:43Z |
| format | Article |
| id | doaj.art-f8fecc0c2fa047ecb2962ae7f8d85564 |
| institution | Directory Open Access Journal |
| issn | 2095-283X 2095-283X |
| language | English |
| last_indexed | 2024-03-09T09:02:43Z |
| publishDate | 2013-06-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj.art-f8fecc0c2fa047ecb2962ae7f8d855642023-12-02T11:21:37ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2095-283X2013-06-012225726410.3724/SP.J.1300.2013.13003One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target TrackingQian Guang-hua0Li Ying1Luo Rong-jian2Chongqing Communication Institute of PLAChongqing Communication Institute of PLAChongqing Communication Institute of PLAThe approach of tracking maneuvering targets based on the “Current” Statistical (CS) model is widely used. The method needs to preset maneuvering frequency and maximum acceleration based on experience. In practice, the preset values are often not consistent with the actual moving state of targets and result in larger tracking errors. In order to tackle the problem, this paper initially deduces a self-adapting maneuvering frequency algorithm from the discrete state equation of the CS model. Then, an improved self-adapting acceleration covariance algorithm is presented. Simulation results show that, by using the self-adapting maneuvering frequency algorithm and the improved self-adapting acceleration covariance algorithm to track targets simultaneously, the ability to self-adapt to the fluctuation of the moving state will be improved. The tracking accuracy is also improved, and the convergence speed of the algorithm is quicker.http://radars.ie.ac.cn/EN/abstract/abstract85.shtml#Maneuvering target tracking“Current&rdquoStatistical (CS) modelManeuvering frequency adaptiveAcceleration variance adaptive |
| spellingShingle | Qian Guang-hua Li Ying Luo Rong-jian One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking Leida xuebao Maneuvering target tracking “Current&rdquo Statistical (CS) model Maneuvering frequency adaptive Acceleration variance adaptive |
| title | One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking |
| title_full | One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking |
| title_fullStr | One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking |
| title_full_unstemmed | One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking |
| title_short | One Maneuvering Frequency and the Variance Adaptive Filtering Algorithm for Maneuvering Target Tracking |
| title_sort | one maneuvering frequency and the variance adaptive filtering algorithm for maneuvering target tracking |
| topic | Maneuvering target tracking “Current&rdquo Statistical (CS) model Maneuvering frequency adaptive Acceleration variance adaptive |
| url | http://radars.ie.ac.cn/EN/abstract/abstract85.shtml# |
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