DocumentCode
1766380
Title
New Integral Transforms for Generalizing the Wigner Distribution and Ambiguity Function
Author
Zhichao Zhang ; Maokang Luo
Author_Institution
Dept. of Math., Sichuan Univ., Chengdu, China
Volume
22
Issue
4
fYear
2015
fDate
42095
Firstpage
460
Lastpage
464
Abstract
The Wigner distribution (WD) and ambiguity function (AF) associated with the linear canonical transform (LCT) play a major role in non-stationary signal processing. Many novel time-frequency analysis tools for it exist, such as the linear canonical WD (LCWD), the linear canonical AF (LCAF), the WD in the LCT domain (WDL) and the AF in the LCT domain (AFL). The purpose of this letter is to introduce new integral transforms that can be regarded as the generalization of LCWD, LCAF, WDL, and AFL. Moreover, the newly defined integral transforms are shown to be useful and effective in filter design in the LCT domain for the separation of multi-component signals and detection of linear frequency-modulated (LFM) signals. The results show that the new integral transforms achieve better detection performance than LCWD, LCAF, WDL, and AFL. Simulations are also performed to verify the rationality and effectiveness of the derived methods.
Keywords
Wigner distribution; signal detection; time-frequency analysis; transforms; AFL; LCAF; LCT domain; LCWD; LFM signals; WDL; Wigner distribution; integral transforms; linear canonical AF; linear canonical WD; linear canonical transform; linear frequency-modulated signals; multicomponent signals; nonstationary signal processing; signal detection; time-frequency analysis tools; Correlation; Equations; Kernel; Signal to noise ratio; Time-frequency analysis; Transforms; Ambiguity function; Wigner distribution; linear canonical transform;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2014.2362616
Filename
6919331
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