| Tracking maneuvering target based on neural fuzzy network with incremental neural leaning |
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| 引用本文： | Liu Mei,Quan Taifan & Yao Tianbin Dept. of Electronic and Communication Engineering,Harbin Inst. of Technology,Harbin 150001,P. R. China. Tracking maneuvering target based on neural fuzzy network with incremental neural leaning[J]. 系统工程与电子技术(英文版), 2006, 17(2): 343-349. DOI: 10.1016/S1004-4132(06)60060-1 |
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| 作者姓名： | Liu Mei Quan Taifan & Yao Tianbin Dept. of Electronic and Communication Engineering Harbin Inst. of Technology Harbin 150001 P. R. China |
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| 作者单位： | Liu Mei，Quan Taifan & Yao Tianbin Dept. of Electronic and Communication Engineering，Harbin Inst. of Technology，Harbin 150001，P. R. China |
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| 基金项目： | This project was supported by Spaceflight Support Fund ( HIT01)，and the Spaceflight Science Project Group |
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| 摘 要： | 1 .INTRODUCTIONIn mixing information battle field,it is necessaryto esti mate the targets sport characteristics for i m-proving efficiency of weapons . The military tacticsguided missile defense system and air detectionsystemneed to track andidentify thousands of tar-getsinreal ti me ,the target informationinclude notonly maneuvering target and not maneuvering tar-gets ,but also environment reverberation and falsealarm. These situations take place in accurateweapon launch system, secondary…
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| 收稿时间： | 2005-02-03 |
Tracking maneuvering target based on neural fuzzy network with incremental neural leaning |
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| Liu Mei,Quan Taifan,Yao Tianbin. Tracking maneuvering target based on neural fuzzy network with incremental neural leaning[J]. Journal of Systems Engineering and Electronics, 2006, 17(2): 343-349. DOI: 10.1016/S1004-4132(06)60060-1 |
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| Authors: | Liu Mei Quan Taifan Yao Tianbin |
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| Affiliation: | Dept. of Electronic and Communication Engineering, Harbin Inst. of Technology, Harbin 150001, P. R. China |
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| Abstract: | The scheme for tracking maneuvering target bas ed on neural fuzzy network with incremental neural learning is proposed. When trac ked target maneuver occurs, the scheme can detect maneuver immediately and estimate the maneuver value accurately , then the tracking filter can be compensated correctly and duly by the estimated maneuver value. When environment changes, neural fuzzy network with incremental neural learning (INL-SONFIN) can find its optimal structure and parameters automatically to adopt to changed environment. So, it always produce estimated output very close to the true maneuver value that leads to good tracking performance and avoids miss-tracking. Sim ulation results show that the performance is superior to the traditional schemes and the scheme can fit changed dynamic environment to track maneuvering target accurately and duly. |
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| Keywords: | neural fuzzy network incremental neural learning maneuvering target tracking |
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