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2003 Fiscal Year Final Research Report Summary

STUDIES ON DETECTION OF SIGNALS IN RANDOM NOISE USING WAVELET-BASED WIGNER DISTRIBUTION

Research Project

Project/Area Number 13650067
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Engineering fundamentals
Research InstitutionKyoto Institute of Technology

Principal Investigator

OHSUMI Akira  KYOTO INSTITUTE OF TECHNOLOGY, FACULTY OF ENGINEERING AND DESIGN, PROFESSOR, 工芸学部, 教授 (70027902)

Co-Investigator(Kenkyū-buntansha) SAWADA Nagato  KYOTO INSTITUTE OF TECHNOLOGY, FACULTY OF ENGINEERING AND DESIGN, RESEARCH ASSOCIATE, 工芸学部, 助手 (80273548)
OHSE Nagato  KYOTO INSTITUTE OF TECHNOLOGY, FACULTY OF ENGINEERING AND DESIGN, LECTURER, 工芸学部, 講師 (70027928)
Project Period (FY) 2001 – 2003
Keywordstime-frequency analvsis / wavelet / winger distribution / maximum likelihood estimation
Research Abstract

The signal detection in random noise is one of important topics in the signal processing community. The purpose of this research work was mainly twofold: (i) to propose a useful method of detecting signals which is contaminated by high random noise, and (ii) to develop an effective approach to problem of estimating the unknown parameters of the noisy signals.
(I) Propose of Wavelet-based Wigner Distribution:
The Wigner distribution (WD) is recognized as one of powerful tools to detect the signal in random noise, and can depicts the concentrated picture in time-frequency domain, However, the use of WD causes the problem of cross terms or interference terms. To cope with such problem, a useful method was proposed in this research works by incorporating the wavelet with WD ; that is, the conventional WD is the Fourier transform of the (naked) covariance of the observation data, while the proposed one is modified as the kind of wavelet transformation of covariance. By simulation studied it wasverfind that the proposed wavelet wavelet-based WD has considerably better behavior with regard to the undesirable cross terms than the conventional WD.
(ii) Development of Effective Parameter Estimation:
In this work the time-delay and frequency-modulation of the received signal taken as unknown parameters to be detected. The useof the conventional WD is impossible to determine their exact values from the time-frequency picture. In this research, a novel approach was developed to this problem by formulating the likelihood function from the realizations of WD random field. This approach can be considered to be the most effective among the existing methods, since this is so tough for high noise such as the signal-to-noise ratio (SNR) -10[dB].

  • Research Products

    (10 results)

All Other

All Publications (10 results)

  • [Publications] A.Ohsumi: "Maximum Likelihood Estimation for Signal Parameters Using Pseudo-Wigner Distribution"Proc.SICE Annual Conference2002. 1598-1603 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 井嶋, 大住, I.Djurovic, 佐藤, 大倉: "不規則雑音に埋もれた信号の未知のパラメータ推定:擬似ウィグナー分布によるアプローチ"電子情報通信学会論文誌A. J86-A. 1158-1169 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] A.Ohsumi, H.Ijima, T.Sodeoka: "High Resolution Detector for Signals in Random Noise using Wavelet-based Wigner Distribution"Proceedings of 25th IEEE International Conference on Acoustics, Speech, and Signal Processing. 596-599 (2000)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] H.Ijima, A.Ohsumi, T.Sodeoka, H.Sato: "The Enhanced Detector of Noisy Signals Using Pseudo-Wigner Distribution"Proceedings of IASTED International Conference Signal Processing, Pattern Recognition and Applications. 95-100 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] I.Djurovic, S.Stankovic, A.Ohsumi, H.Ijima: "Estimation of Line Parameters Using SLIDE Algorithm and TF Representations"Proceedings of 9th IEEE International Conference on Electronics, Circuit and Systems. vol.3. 1067-1070 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] A.Ohsumi: "Maximum likelihood Estimation for Signal Parameters Using Pseudo-Wigner Distribution"Proc.SICE Annual Conference2002. 1598-1603 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] A.Ohsumi, H.ijima, I.Djurovic, H.Sato, H.Okura: "Parameter Estimation of Signals in Random Noise: An Approach Using Pseudo-Wigner Distribution"Trans.IEICE, Ser. A. vol.J86-A no.11. 1158-1169 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] A.Ohsumi, H.Ijima, T.Sodeoka: "High Resolution Detector for Signals in Random Noise using Wavelet-based Wigner Distribution"Proceedings of 25th IEEE International Conference on Acoustics, Speech, and Signal Processing. 596-599 (2000)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] H.Ijima, A.Ohaumi, T.Sodeoka, H.sato: "The Enhanced Detector of Noisy Signals Using Pseudo-Wigner Distribution"Proceedings of IASTED International Conference Signal Processing, Pattern Recognition and Applications. 95-100 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I.Djurovic, S.Stankovic, A.Ohsumi, H.Ijima: "Estimation of Line Parameters Using SLIDE Algorithm and TF Representations"Proceedings of 9th IEEE International Conference on Electronics, Circuit and Systems. 1067-1070 (2002)

    • Description
      「研究成果報告書概要(欧文)」より

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Published: 2005-04-19  

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