Infrared Counter-Countermeasure Efficient Techniques using Neural Network, Fuzzy System and Kalman Filter

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%.