NDLI: Radar target classification based on support vector machines and High Resolution Range Profiles

Content Provider	IEEE Xplore Digital Library
Author	Kent, S. Kasapoglu, N.G. Kartal, M.
Copyright Year	2008
Description	Author affiliation: Dept. of Electron. & Commun., Istanbul Tech. Univ., Istanbul (Kent, S.; Kasapoglu, N.G.; Kartal, M.)
Abstract	In this study, the support vector machine (SVM) was used as a classifier to identify aerospace objects. Radar target identification based on high resolution range profiles (HRRPs) received much attention because of its reduced complexity than those using two-dimensional (2-D) ISAR images. Therefore range profiles were used as feature vectors to represent radar data. Data sets which are for training and testing were generated by using a program called radar target backscattering simulation (RTBS) for three different target types. The performance of the SVM was compared with other classification algorithms including statistical classification techniques such as maximum likelihood (ML) and fisher linear likelihood (FLL).
Starting Page	1
Ending Page	6
File Size	3183393
Page Count	6
File Format	PDF
ISBN	9781424415380
ISSN	10975659
DOI	10.1109/RADAR.2008.4721107
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support vector machine classification Radar imaging Radar scattering Electromagnetic scattering Signal processing algorithms Fourier transforms Discrete wavelet transforms Image resolution Signal resolution high resolution range profile (HRRP) Support vector machine (SVM) target classification
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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