Target recognition by self-organizing map (SOM) type unsupervised clustering using electromagnetic scattered signals in resonance region

Date

2010-12-20

Author

Sayan, Gönül
Sayan, Eren Sila

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This paper investigates the use of unsupervised learning for electromagnetic target recognition in resonance region. Wigner distribution based target features extracted from late-time target responses at arbitrarily observed aspect angles are used to design a target classifier by using the self-organized map (SOM) algorithm. Effects of having unequal amounts of training data for different library targets are investigated in particular. Small scale aircraft modeled by conducting wires are used as test targets in demonstrations. © 2010 IEEE.

Subject Keywords

Unsupervised learning, Self organizing map

URI

https://hdl.handle.net/11511/57790

DOI

https://doi.org/10.1109/mmw.2010.5605193

Conference Name

10th Mediterranean Microwave Symposium

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Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

G. Sayan and E. S. Sayan, “Target recognition by self-organizing map (SOM) type unsupervised clustering using electromagnetic scattered signals in resonance region,” presented at the 10th Mediterranean Microwave Symposium, Guzelyurt, Cyprus, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57790.