جلد 5، شماره 4 - ( 9-1388 )                   جلد 5 شماره 4 صفحات 215-222 | برگشت به فهرست نسخه ها


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Mosavi M R. Infrared Counter-Countermeasure Efficient Techniques using Neural Network, Fuzzy System and Kalman Filter. IJEEE. 2009; 5 (4) :215-222
URL: http://ijeee.iust.ac.ir/article-1-215-fa.html
Infrared Counter-Countermeasure Efficient Techniques using Neural Network, Fuzzy System and Kalman Filter. . 1388; 5 (4) :215-222

URL: http://ijeee.iust.ac.ir/article-1-215-fa.html


چکیده:   (7296 مشاهده)
This paper presents design and implementation of three new Infrared Counter-Countermeasure (IRCCM) efficient methods using Neural Network (NN), Fuzzy System (FS), and Kalman Filter (KF). The proposed algorithms estimate tracking error or correction signal when jamming occurs. An experimental test setup is designed and implemented for performance evaluation of the proposed methods. The methods validity is verified with experiments on IR seeker reticle based on a Digital Signal Processing (DSP) processor. The practical results emphasize that the proposed algorithms are highly effective and can reduce the jamming effects. The experimental results obtained strongly support the potential of the method using FS to eliminate the IRCM effect 83%.
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نوع مطالعه: Research Paper | موضوع مقاله: 3-Filtering , Smoothing & Estimation
دریافت: ۱۳۸۸/۹/۲۱ | پذیرش: ۱۳۹۲/۱۰/۹ | انتشار: ۱۳۹۲/۱۰/۹

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