Multilayer Neural Network-Burg Combination for Acoustical Detection of Buried Objects

Multilayer Neural Network-Burg Combination
for Acoustical Detection of Buried Objects

      Mujahid AL-Azzo1 and Lubna Badri2‎
‎1Faculty of Engineering Technology, Zarqa Private University, Jordan
‎2Faculty of Engineering, Philadelphia University, Jordan



Abstract: A Burg technique is employed to model the long wavelength localization and imaging problem. A Burg method is used as a ‎high resolution and stable technique. The idea of in-line holography is used to increase the ratio of the signal to noise due to ‎the effect of concealing media that decreases the value of the received signal. The performance is enhanced by using ‎multilayer neural network for noise reduction. The aim of using multilayer neural network is to extract the essential ‎knowledge from a noisy training data. Theoretical and experimental results have showed that preprocessing the noisy data ‎with multilayer neural network will decrease the effect of noise as much as possible. Applying the enhanced data to spectral ‎estimation methods has improved the performance of the model. A comparison is made for the two cases: with and without ‎application of neural network for different values of signal to noise ratio. Also, the performance is investigated for different ‎numbers of samples.‎

Keywords: Multilayer neural networks, holographic imaging, burg method, and modelling.‎

Received November 13, 2008; accepted August 3, 2009‎
Read 5613 times Last modified on Wednesday, 13 October 2010 05:21
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