NDLI: A Novel Radar Target Recognition Algorithm Based on SVM

Content Provider	IEEE Xplore Digital Library
Author	Junxian Li Limin Shen Shuo Yang
Copyright Year	2008
Description	Author affiliation: Mil. Representatives Room of PLA in CAMA, Luoyang (Shuo Yang) \|\| Electron. Inf. Eng. Coll., Henan Univ. of Sci. & Technol., Luoyang (Junxian Li; Limin Shen)
Abstract	To solve the problems and defections of existing methods of support vector machine (SVM) classification, an improved Gaussian kernel based on SVM is proposed and a improved SVM model selection scheme combining leave-one-Out method with one-validation method is presented in this paper, Based on the high resolution range profile (HRRP) of three types of target, a preprocessing method is introduced, the novel classification algorithm for HRRP based on the improved SVM is applied. Finally, experimental results prove that the improved SVM classifier has better performance on target-aspect stability, training set-size stability and anti-noise ability than traditional SVM.
Starting Page	431
Ending Page	434
File Size	158091
Page Count	4
File Format	PDF
ISBN	9780769535050
DOI	10.1109/IITA.Workshops.2008.191
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gaussian kernel Target recognition Stability Statistical learning Radar tracking Radar Target Recognition Support vector machines Diversity reception Support vector machine classification Signal processing algorithms Radar imaging classifier Kernel algorithm
Content Type	Text
Resource Type	Article

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