Transmitter individual identification based on local surrounding-line integral bispectrum

Author

Tang Tongwei ; Tao Wanglin

Author_Institution

Sch. of Electr. Inf. Eng., Lanzhou Jiaotong Univ., Lanzhou, China

fYear

2012

fDate

9-11 Nov. 2012

Firstpage

1

Lastpage

5

Abstract

Based on the research of identifying individual radio transmitters with the same model, a novel method for identifying individual radio transmitters with the local surrounding-line integral bispectrum is proposed. The selected spectra and parameters are significant for classification of the received signal from the identification feature vector, and support vector machine based on mixed kernel function is used to realize the individual identification. The experimental results demonstrate that the suggested technique has a recognition rate of 90% in a low signal noise ratio, and it can solve the problem of identifying individual transmitters with the same model and manufacturing lot.

Keywords

feature extraction; radio transmitters; signal classification; support vector machines; identification feature vector; individual radio transmitter identification; local surrounding-line integral bispectrum; mixed kernel function; signal classification; signal noise ratio; support vector machine; transmitter individual identification; Educational institutions; Feature extraction; Fingerprint recognition; Kernel; Radio transmitters; Support vector machine classification; Support Vector Machine (SVM); integral bispectrum; local surrounding-line; mixed kernel function; radio transmitters;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Signal Processing (IASP), 2012 International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-2547-9

Type

conf

DOI

10.1109/IASP.2012.6425014

Filename

6425014