Frequency-Hopping Transmitter Fingerprint Feature Classification Based on Kernel Collaborative Representation Classifier
Joint Authors
Guo, Ying
Li, Hongguang
Sui, Ping
Zhang, Kun-feng
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-09
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Noncooperation frequency-hopping (FH) transmitter fingerprint feature classification is a significant but challenging issue for FH transmitter recognition, since not only is it sensitive to noise but also it has the nonlinear, non-Gaussian and nonstability characteristics, which make it difficult to guarantee the classification in the original signal space.
To address these problems, a method of frequency-hopping transmitter fingerprint feature classification based on kernel collaborative representation classifier is proposed in this paper.
First, the noise suppression pretreatment of the FH transmitter signal is carried out by using the wave atoms frame method.
Then, the nuances of the FH transmitters in the feature space are characterized by the surrounding-line integral bispectra features.
And finally, incorporating the kernel function, a classifier which can generalize a linear algorithm to nonlinear counterpart is constructed for the final transmitter fingerprint feature classification.
Extensive experiments on real-world FH transmitter “turn-on” transient signals demonstrate the robust classification of our method.
American Psychological Association (APA)
Sui, Ping& Guo, Ying& Zhang, Kun-feng& Li, Hongguang. 2017. Frequency-Hopping Transmitter Fingerprint Feature Classification Based on Kernel Collaborative Representation Classifier. Wireless Communications and Mobile Computing،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1206341
Modern Language Association (MLA)
Sui, Ping…[et al.]. Frequency-Hopping Transmitter Fingerprint Feature Classification Based on Kernel Collaborative Representation Classifier. Wireless Communications and Mobile Computing No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1206341
American Medical Association (AMA)
Sui, Ping& Guo, Ying& Zhang, Kun-feng& Li, Hongguang. Frequency-Hopping Transmitter Fingerprint Feature Classification Based on Kernel Collaborative Representation Classifier. Wireless Communications and Mobile Computing. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1206341
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206341