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A new electromagnetic target classification method with MUSIC algorithm
Date
2006-01-01
Author
Secmen, Mustafa
Sayan, Gönül
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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This paper introduces a novel method for aspect invariant electromagnetic target recognition based on the use of multiple signal classification (MUSIC) algorithm to extract late-time resonant target features from the ultra-wideband scattered data. This method is mainly based on the usage of MUSIC spectra obtained from electromagnetic scattered data as the target features. This approach achieves very high accuracy rates even at very low signal-to-noise ratio (SNR) values although it needs scattered data for classifier design at only a few different aspects and makes use of the MUSIC algorithm in a simple and computationally efficient way. Details of the theoretical background, the classifier design process and the results for conducting and dielectric spherical targets will be presented in the following sections.
Subject Keywords
Multiple signal classification
,
Algorithm design and analysis
,
Electromagnetic scattering
,
Target recognition
,
Classification algorithms
,
Data mining
,
Resonance
,
Ultra wideband technology
,
Signal to noise ratio
,
Signal design
URI
https://hdl.handle.net/11511/38050
DOI
https://doi.org/10.1109/siu.2006.1659711
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar