• DocumentCode
    32263
  • Title

    Spectrum Combining for ENF Signal Estimation

  • Author

    Hajj-Ahmad, Adi ; Garg, Radhika ; Min Wu

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
  • Volume
    20
  • Issue
    9
  • fYear
    2013
  • fDate
    Sept. 2013
  • Firstpage
    885
  • Lastpage
    888
  • Abstract
    The Electric Network Frequency (ENF) is the supply frequency of power distribution networks, and is often captured by audio or video measurements recorded near power supplies. The time varying nature of the ENF allows it to be used for such forensic applications as estimating the time and location of media recordings, and discerning their integrity. An initial step in such applications is to extract the ENF signal-instantaneous ENF values over time-as accurately as possible. Existing techniques rely on estimating the ENF around the nominal frequency of 50/60 Hz, or around one of its harmonics at a time. In this letter, a novel spectrum combining approach is proposed, which exploits the presence of the ENF around different harmonics of the nominal frequency. The ENF signal is estimated by combining the ENF at multiple harmonics, based on the local signal-to-noise ratio at each harmonic. A hypothesis testing performance of an ENF-based timestamp verification application is examined to validate that the proposed approach achieves a more robust and accurate performance than conventional ENF estimation techniques.
  • Keywords
    distribution networks; estimation theory; harmonics; signal processing; ENF signal estimation; audio measurements; electric network frequency; harmonics; power distribution networks; signal-to-noise ratio; spectrum combining; supply frequency; video measurements; Equations; Estimation; Frequency estimation; Harmonic analysis; Power system harmonics; Signal to noise ratio; Electric Network Frequency; spectrum combining; timestamp verification;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2013.2272523
  • Filename
    6557080