Intelligent target recognition based on wavelet packet neural network

• Published in: Expert systems with applications Vol. 29; no. 1; pp. 175 - 182
• Main Authors: Avci, Engin, Turkoglu, Ibrahim, Poyraz, Mustafa
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2005
• Subjects: Entropy; Feature extraction; Intelligent system; Pattern recognition; Radar target echo signal; Wavelet packet decomposition; Wavelet packet neural networks; Wavelet packet decomposition; Feature extraction; Wavelet packet neural networks; Entropy; Pattern recognition; Radar target echo signal; Intelligent system
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2005.01.016

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.