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Electromagnetic target classification using time–frequency analysis and neural networks

✍ Scribed by Gönül Turhan-Sayan; Kemal Leblebicioglu; Türker Ince

Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
161 KB
Volume
21
Category
Article
ISSN
0895-2477

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✦ Synopsis

This paper demonstrates the feasibility and ad¨antages of ( ) using a self-organizing map SOM -type neural network classifier for electromagnetic target recognition. The classifier is supported by a no¨el ( ) feature extraction unit in which the Wigner distribution WD , a time᎐ frequency representation, is utilized for the extraction of naturalresonance-related energy feature ¨ectors from scattered fields. The proposed target classification technique is tested for a set of canonical targets, displaying an excellent performance in terms of both real-time classification speed and accuracy, e¨en in the presence of noisy data.

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