Variance-SNR Based Noise Suppression on Linear Canonical Choi-Williams Distribution of LFM Signals

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外文摘要：By solving the existing expectation-sig-nal-to-noise ratio(expectation-SNR)based inequality model of the closed-form instantaneous cross-correlation function type of Choi-Williams distribution(CICFCWD),the linear canonical transform(LCT)free parameters se-lection strategies obtained are usually unsatisfactory.Since the second-order moment variance outperforms the first-order moment expectation in accurately characteriz-ing output SNRs,this paper uses the variance analysis technique to improve parameters selection strategies.The CICFCWD's average variance of deterministic signals em-bedded in additive zero-mean stationary circular Gaussi-an noise processes is first obtained.Then the so-called variance-SNRs are defined and applied to model a vari-ance-SNR based inequality.A stronger inequalities sys-tem is also formulated by integrating expectation-SNR and variance-SNR based inequality models.Finally,a dir-ect application of the system in noisy one-component and bi-component linear frequency-modulated(LFM)signals detection is studied.Analytical algebraic constraints on LCT free parameters newly derived seem more accurate than the existing ones,achieving better noise suppression effects.Our methods have potential applications in optic-al,radar,communication and medical signal processing.

外文关键词：

Average varianceChoi-Williams dis-tributionLinear canonical transformLinear frequency-modulated signal

作者：

ZHANG Zhichao

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作者单位：

School of Mathematics and Statistics,Nanjing University of Information Science and Technology,Nanjing 210044,China

School of Computer Science and Engineering,Macau University of Science and Technology,Macau 999078,China

基金：

国家自然科学基金江苏省自然科学基金Jiangsu Planned Projects for Postdoctoral Research FundsNatural Science Foundation of the Jiangsu Higher Education Institutions of ChinaJiangsu Province High-Level Innovative and Entrepreneurial Talent Introduction ProgramMacau Young Scholars ProgramStartup Foundation for Introducing Talent of NUIST

项目编号：

61901223BK201907692021K205B19KJB510041R2020SCB55AM20200152019r024

出版年：

2022

DOI：

10.1049/cje.2020.00.367

电子学报(英文)

CSTPCDSCIEI

ISSN：1022-4653

年,卷(期)：2022.31(5)

参考文献量4