Intelligent target recognition based on wavelet packet neural network

Authors:
Engin Avci;Ibrahim Turkoglu;Mustafa Poyraz
Affiliations:
Department of Electronic and Computer Science, Firat University, 23119 Elazig, Turkey;Department of Electronic and Computer Science, Firat University, 23119 Elazig, Turkey;Department of Electric and Electronic, Engineering Faculty, Firat University, 23119 Elazig, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2005

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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 packet neural network model developed by us is used. The model consists of two layers: wavelet and multi-layer perceptron. The wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of wavelet packet decomposition and wavelet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the developed system has been evaluated in noisy radar target echo (RTE) signals. The test results showed that this system was effective in detecting real RTE signals. The correct classification rate was about 95% for used target subjects.