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Tracking abrupt frequency changes

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  • Ta‐Hsin Li
  • Benjamin Kedem

Abstract

This paper addresses the problem of accurate estimation and rapid adaptation of abrupt frequency changes from noisy sinusoidal signals. A two‐filter adaptive algorithm is proposed to achieve the seemingly contradictory objectives. This algorithm is derived from an iterative batch procedure that has been proved to yield consistent and asymptotically Gaussian estimates for constant‐frequency estimation. These properties provide a basis for the detection of abrupt changes in the time‐varying frequency. Combining the high accuracy of narrow‐band/long‐memory filtering with the high adaptability of wide‐band/short‐memory filtering, the two‐filter approach is particularly suitable for tracking time‐varying frequencies that can be approximately modeled as piecewise‐constant functions of time. Simulation results are reported that justify the viability of the method.

Suggested Citation

  • Ta‐Hsin Li & Benjamin Kedem, 1998. "Tracking abrupt frequency changes," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(1), pages 69-82, January.
    • Handle: RePEc:bla:jtsera:v:19:y:1998:i:1:p:69-82
    DOI: 10.1111/1467-9892.00077
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    Cited by:

    1. Song, Kai-Sheng & Li, Ta-Hsin, 2000. "A statistically and computationally efficient method for frequency estimation," Stochastic Processes and their Applications, Elsevier, vol. 86(1), pages 29-47, March.
    2. Chen, Bei & Gel, Yulia R., 2010. "Autoregressive frequency detection using Regularized Least Squares," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1712-1727, August.

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