View in EDS

IF estimation of FSK signals using adaptive smoothed windowed cross Wigner–Ville distribution.

Saved in:
Bibliographic Details
Title: IF estimation of FSK signals using adaptive smoothed windowed cross Wigner–Ville distribution.
Authors: Chee, Yen Mei1,2 ym.chee@kdu.edu.my, Sha’ameri, Ahmad Zuri2 ameri-zuri@fke.utm.my, Zabidi, Muhammad Munim Ahmad2
Source: Signal Processing. Jul2014, Vol. 100, p71-84. 14p.
Subjects: Signals & signaling, Adaptive computing systems, Smoothing (Numerical analysis), Wigner distribution, Time-varying systems, Frequency shift keying
Abstract: Abstract: Time-varying signals such as frequency shift-keying (FSK) signals can be characterized by the instantaneous frequency (IF). From the estimated IF, it is possible to derive the signal modulation parameters such as the subcarrier frequencies and the symbol duration. If accurate time–frequency representation (TFR) is obtained, the cross time–frequency distribution (XTFD) provides an optimum solution to IF estimation over quadratic time–frequency distribution (QTFD). Thus, an adaptive XTFD is proposed, the adaptive smoothed windowed cross Wigner–Ville distribution (ASW-XWVD), for which the kernel parameters are estimated according to the signal characteristics and the choice of reference signal. The IF is estimated from the peak of the TFR and comparison is performed using the S-transform. The variance in the IF estimation using the proposed ASW-XWVD meets the Cramer–Rao lower bound (CRLB) at minimum signal-to-noise ratio (SNR) of −3dB, while the S-transform never meets the CRLB, even at SNR of 12dB. For practical applications, the ASW-XWVD is applied to the FSK signal in the high frequency (HF) band and is able to provide accurate TFR and IF estimates at SNR of 14dB. [Copyright &y& Elsevier]
Copyright of Signal Processing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 94692879
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: IF estimation of FSK signals using adaptive smoothed windowed cross Wigner–Ville distribution.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Chee%2C+Yen+Mei%22">Chee, Yen Mei</searchLink><relatesTo>1,2</relatesTo><i> ym.chee@kdu.edu.my</i><br /><searchLink fieldCode="AR" term="%22Sha’ameri%2C+Ahmad+Zuri%22">Sha’ameri, Ahmad Zuri</searchLink><relatesTo>2</relatesTo><i> ameri-zuri@fke.utm.my</i><br /><searchLink fieldCode="AR" term="%22Zabidi%2C+Muhammad+Munim+Ahmad%22">Zabidi, Muhammad Munim Ahmad</searchLink><relatesTo>2</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Signal+Processing%22">Signal Processing</searchLink>. Jul2014, Vol. 100, p71-84. 14p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Signals+%26+signaling%22">Signals & signaling</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+computing+systems%22">Adaptive computing systems</searchLink><br /><searchLink fieldCode="DE" term="%22Smoothing+%28Numerical+analysis%29%22">Smoothing (Numerical analysis)</searchLink><br /><searchLink fieldCode="DE" term="%22Wigner+distribution%22">Wigner distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Time-varying+systems%22">Time-varying systems</searchLink><br /><searchLink fieldCode="DE" term="%22Frequency+shift+keying%22">Frequency shift keying</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Abstract: Time-varying signals such as frequency shift-keying (FSK) signals can be characterized by the instantaneous frequency (IF). From the estimated IF, it is possible to derive the signal modulation parameters such as the subcarrier frequencies and the symbol duration. If accurate time–frequency representation (TFR) is obtained, the cross time–frequency distribution (XTFD) provides an optimum solution to IF estimation over quadratic time–frequency distribution (QTFD). Thus, an adaptive XTFD is proposed, the adaptive smoothed windowed cross Wigner–Ville distribution (ASW-XWVD), for which the kernel parameters are estimated according to the signal characteristics and the choice of reference signal. The IF is estimated from the peak of the TFR and comparison is performed using the S-transform. The variance in the IF estimation using the proposed ASW-XWVD meets the Cramer–Rao lower bound (CRLB) at minimum signal-to-noise ratio (SNR) of −3dB, while the S-transform never meets the CRLB, even at SNR of 12dB. For practical applications, the ASW-XWVD is applied to the FSK signal in the high frequency (HF) band and is able to provide accurate TFR and IF estimates at SNR of 14dB. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Signal Processing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=94692879
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.sigpro.2013.12.031
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 71
    Subjects:
      – SubjectFull: Signals & signaling
        Type: general
      – SubjectFull: Adaptive computing systems
        Type: general
      – SubjectFull: Smoothing (Numerical analysis)
        Type: general
      – SubjectFull: Wigner distribution
        Type: general
      – SubjectFull: Time-varying systems
        Type: general
      – SubjectFull: Frequency shift keying
        Type: general
    Titles:
      – TitleFull: IF estimation of FSK signals using adaptive smoothed windowed cross Wigner–Ville distribution.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Chee, Yen Mei
      – PersonEntity:
          Name:
            NameFull: Sha’ameri, Ahmad Zuri
      – PersonEntity:
          Name:
            NameFull: Zabidi, Muhammad Munim Ahmad
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: Jul2014
              Type: published
              Y: 2014
          Identifiers:
            – Type: issn-print
              Value: 01651684
          Numbering:
            – Type: volume
              Value: 100
          Titles:
            – TitleFull: Signal Processing
              Type: main
ResultId 1