• DocumentCode
    1957693
  • Title

    Application of frequency estimation method based on Hilbert-Huang transform to non-cooperative information source

  • Author

    Chen Wei-jun ; Jing Zhan-Rong ; Xu Zhen-Hua ; Yuan Fang-Fei

  • Author_Institution
    Coll. of Electron. & Inf., Northwestern Polytech. Univ., Xi´An, China
  • Volume
    5
  • fYear
    2010
  • fDate
    9-11 July 2010
  • Firstpage
    315
  • Lastpage
    319
  • Abstract
    Frequency estimation in passive location based on non-cooperative information sources plays an important role. And existing methods such as wavelet transform (WT) can´t satisfy the precision of frequency estimation what is needed in location. In order to solve the puzzle, the Hilbert-Huang transform(HHT) is adopted in this article. HHT is based on the local characteristics of signals, which is an adaptive and efficient transformation method. It can not only overcome the disadvantages of quantitative time and frequency analysis in WT, but also it is particularly suitable for analyzing the nonlinear and non-stationary signals such as broadcasting signal, GSM signal etc. In this paper, we choose three typical kinds of signal to estimate their frequency. The original signal is first decomposed by Empirical Mode Decomposition(EMD), all intrinsic mode functions (IMF) will be acquired. Secondly we perform Hilbert Transform for them and gained signal´s Hilbert amplitude spectrum, and signal´s frequency component needed in location will be drawn and found in the end. The analysis results from simulated signals and experimental signals have verified the feasibility and precision of the method in frequency measurement of sine signal along with Gauss complex circle flat noise, the noiseproof feature is also wonderful, in the condition of which Signal-to-noise Ratio is greater than or equal to 5dB, for all kinds of modulation signal of the location technology, the estimated accuracy is suitable for the project.
  • Keywords
    Gaussian noise; Hilbert transforms; frequency estimation; signal processing; wavelet transforms; Gauss complex circle flat noise; Hilbert amplitude spectrum; Hilbert-Huang transform; empirical mode decomposition; frequency estimation; intrinsic mode function; noncooperative information sources; passive location; signal frequency component; signal-to-noise ratio; sine signal frequency measurement; wavelet transform; Biology; GSM; Empirical Mode Decomposition; Hilbert-Huang Transform (HHT); frequency estimation; intrinsic mode function; passive location; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5537-9
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2010.5565016
  • Filename
    5565016