Intelligent target recognition based on wavelet adaptive network based fuzzy inference system

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Abstract

In this paper, an intelligent target recognition system is presented for target recognition from target echo signal of High Resolution Range (HRR) radars. This paper especially deals with combination of the feature extraction and classification from measured real target echo signal waveforms using X-band pulse radar. Because of this, a wavelet adaptive network based fuzzy inference system model developed by us is used. The model consists of two layers: wave-let and adaptive network based fuzzy inference system. The wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of wavelet decomposition and wavelet entropy. The used for classification is an adaptive network based fuzzy inference system. The performance of the developed system has been evaluated in noisy radar target echo signals. The test results showed that this system was effective in detecting real radar target echo signals. The correct classification rate was about 93% for used target subjects. © Springer-Verlag Berlin Heidelberg 2005.

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Avci, E., Turkoglu, I., & Poyraz, M. (2005). Intelligent target recognition based on wavelet adaptive network based fuzzy inference system. In Lecture Notes in Computer Science (Vol. 3522, pp. 594–603). Springer Verlag. https://doi.org/10.1007/11492429_72

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