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Volume & Issue no: Volume 3, Issue 11, November 2014

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Title:
Target Classification in Forward Scattering Radar in Noisy Environment
Author Name:
Mohamed Khala Alla H.M, Mohamed Kanona and Ashraf Gasim Elsid
Abstract:
ABSTRACT Forward scattering radar (FSR) is a special case of bistatic radar that can be used for automatic ground target detection and classification, the interest in FSR is rises after its capability in target classification is validated. The recent development of the FSR system for ground target classifications did not consider a rough environment analysis. This paper introduces and analyze and study to the automatic ground target classification using Neural network under different noisy conditions this include the overall classification system and the extraction of features from the radar measurements provided results have shown the effectiveness of neural network as potential classifier for ground targets even in sever noisy environment Keywords: Forward Scattering Radar, Neural network, Signal to noise ratio
Cite this article:
Mohamed Khala Alla H.M, Mohamed Kanona and Ashraf Gasim Elsid , " Target Classification in Forward Scattering Radar in Noisy Environment " , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 3, Issue 11, November 2014 , pp. 188-192 , ISSN 2319 - 4847.
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