Multi-component LFM signal feature extraction based on improved wigner-hough transform

Feng Liu; Da Peng Sun; Yu Huang; Ran Tao; Yue Wang

Multi-component LFM signal feature extraction based on improved wigner-hough transform

Feng Liu^*, Da Peng Sun, Yu Huang, Ran Tao, Yue Wang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

Feature extraction of multi-component LFM signal based on Wigner-Hough transform is generally plagued by noises. Faced with this problem, the improved Sobel operator of digital image processing is used to detect edge features of Wigner-Ville distribution (WVD) figure of signals with noise, and then signal characteristics can be extracted well and truly under Hough transform. Through computer simulation of the Wigner-Hough transform (WHT), SPWD-Hough transform and improving WHT, feature extraction result of multi-component LFM signal using improved WHT proved to be the best.

Original language	English
Pages (from-to)	914-917
Number of pages	4
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	28
Issue number	10
Publication status	Published - Oct 2008

Keywords

Feature extraction
Multi-component LFM signal
Sobel operator
Wigner-Hough transform

Cite this

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title = "Multi-component LFM signal feature extraction based on improved wigner-hough transform",

abstract = "Feature extraction of multi-component LFM signal based on Wigner-Hough transform is generally plagued by noises. Faced with this problem, the improved Sobel operator of digital image processing is used to detect edge features of Wigner-Ville distribution (WVD) figure of signals with noise, and then signal characteristics can be extracted well and truly under Hough transform. Through computer simulation of the Wigner-Hough transform (WHT), SPWD-Hough transform and improving WHT, feature extraction result of multi-component LFM signal using improved WHT proved to be the best.",

keywords = "Feature extraction, Multi-component LFM signal, Sobel operator, Wigner-Hough transform",

author = "Feng Liu and Sun, {Da Peng} and Yu Huang and Ran Tao and Yue Wang",

year = "2008",

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language = "English",

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T1 - Multi-component LFM signal feature extraction based on improved wigner-hough transform

AU - Liu, Feng

AU - Sun, Da Peng

AU - Huang, Yu

AU - Tao, Ran

AU - Wang, Yue

PY - 2008/10

Y1 - 2008/10

N2 - Feature extraction of multi-component LFM signal based on Wigner-Hough transform is generally plagued by noises. Faced with this problem, the improved Sobel operator of digital image processing is used to detect edge features of Wigner-Ville distribution (WVD) figure of signals with noise, and then signal characteristics can be extracted well and truly under Hough transform. Through computer simulation of the Wigner-Hough transform (WHT), SPWD-Hough transform and improving WHT, feature extraction result of multi-component LFM signal using improved WHT proved to be the best.

AB - Feature extraction of multi-component LFM signal based on Wigner-Hough transform is generally plagued by noises. Faced with this problem, the improved Sobel operator of digital image processing is used to detect edge features of Wigner-Ville distribution (WVD) figure of signals with noise, and then signal characteristics can be extracted well and truly under Hough transform. Through computer simulation of the Wigner-Hough transform (WHT), SPWD-Hough transform and improving WHT, feature extraction result of multi-component LFM signal using improved WHT proved to be the best.

KW - Feature extraction

KW - Multi-component LFM signal

KW - Sobel operator

KW - Wigner-Hough transform

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M3 - Article

AN - SCOPUS:55949123027

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JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

IS - 10

ER -

Multi-component LFM signal feature extraction based on improved wigner-hough transform

Abstract

Keywords

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