Pulse doppler radar target recognition using a two-stage SVM procedure
Author
Eryildirim, A.
Onaran, I.
Date
2010-07-07Source Title
IEEE Transactions on Aerospace and Electronic Systems
Print ISSN
0018-9251
Publisher
IEEE
Volume
47
Issue
2
Pages
1450 - 1457
Language
English
Type
ArticleItem Usage Stats
143
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121
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Abstract
It is possible to detect and classify moving and stationary targets using ground surveillance pulse-Doppler radars (PDRs). A two-stage support vector machine (SVM) based target classification scheme is described here. The first stage tries to estimate the most descriptive temporal segment of the radar echo signal and the target signal is classified using the selected temporal segment in the second stage. Mel-frequency cepstral coefficients of radar echo signals are used as feature vectors in both stages. The proposed system is compared with the covariance and Gaussian mixture model (GMM) based classifiers. The effects of the window duration and number of feature parameters over classification performance are also investigated. Experimental results are presented.
Keywords
Classification performanceFeature parameters
Feature vectors
Gaussian mixture model
Ground surveillance
Mel-frequency cepstral coefficients
Pulse-doppler radar
Radar echoes
Stationary targets
Target classification
Target signals
Temporal segments
Two stage
Doppler effect
Doppler radar
Radar
Radar target recognition
Permalink
http://hdl.handle.net/11693/21974Published Version (Please cite this version)
http://dx.doi.org/10.1109/TAES.2011.5751269Collections
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