• DocumentCode
    775389
  • Title

    Two algorithms for adaptive retrieval of slowly time-varying multiple cisoids in noise

  • Author

    Tichavsky, Petr ; Handel, Peter

  • Author_Institution
    Inst. of Inf. Theory & Autom., Prague, Czech Republic
  • Volume
    43
  • Issue
    5
  • fYear
    1995
  • fDate
    5/1/1995 12:00:00 AM
  • Firstpage
    1116
  • Lastpage
    1127
  • Abstract
    Two algorithms for tracking parameters of slowly varying multiple complex sine waves (cisoids) in noise (the multiple frequency tracker and the adaptive notch filter) are described. For high signal-to-noise ratio (SNR), the properties of the algorithms (i.e., stability, noise rejection, and tracking speed) are studied analytically using a linear filter approximation technique. The tradeoff between noise rejection and tracking error for both algorithms is shown to be similar. Different choices of the design variables are discussed, namely (i) minimal mean-square estimation error for random walk modeled frequency variations and (ii) minimal stationary estimation variance subject to a given tracking delay
  • Keywords
    adaptive signal processing; approximation theory; delay circuits; delays; error analysis; noise; notch filters; parameter estimation; prediction theory; tracking filters; SNR; adaptive notch filter; adaptive retrieval; design variables; high signal-to-noise ratio; linear filter approximation; minimal mean-square estimation error; minimal stationary estimation variance; multiple complex sine waves; multiple frequency tracker; noise rejection; parameters tracking; random walk modeled frequency variations; recursive prediction error algorithm; slowly time-varying multiple cisoids; stability; tracking delay; tracking error; tracking speed; Adaptive filters; Algorithm design and analysis; Approximation algorithms; Delay estimation; Frequency estimation; Linear approximation; Nonlinear filters; Signal analysis; Signal to noise ratio; Stability analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.382397
  • Filename
    382397