Gabor Filter Approach to Joint Feature Extraction and Target Recognition

This paper presents a new approach of improving automatic target recognition (ATR) performance by tuning adaptively the Gabor filter. The Gabor filter adopts the network structure of two layers, and its input layer constitutes the adaptive nonlinear feature extraction part, whereas the weights betwe...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2009-01, Vol.45 (1), p.17-30
Main Authors: Feng Zhu, Feng Zhu, Xian-Da Zhang, Xian-Da Zhang, Ya-Feng Hu, Ya-Feng Hu
Format: Article
Language:English
Subjects:
Adaptive filters
Adaptive structures
Aircraft components
Electronic systems
Feature extraction
Fourier transforms
Gabor filters
Information science
Pattern classification
Radar imaging
Recognition
Statistics
Target recognition
Time frequency analysis
Tuning
Vectors
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Summary:This paper presents a new approach of improving automatic target recognition (ATR) performance by tuning adaptively the Gabor filter. The Gabor filter adopts the network structure of two layers, and its input layer constitutes the adaptive nonlinear feature extraction part, whereas the weights between output layer and input layer constitute the linear classifier. From the statistic property of high-resolution range profile (HRRP), its extracted nonstationarity degree of features is tracked to extract the discriminative features of Gabor atoms. Two experimental examples show that the Gabor filter approach with simple structure has higher recognition rate in radar target recognition from HRRP as compared with several existing methods.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2009.4805260