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Abstract
The problem of extraction/elimination of nonstationary sinusoidalsignals from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS)algorithm can be employed to perform many off-line signal processing tasks, such as elimination of sinusoidal interference from a prerecorded signal. In the single sinusoid case, we show that when the unknown signal frequency drifts accordingto the random-walk model, the optimally tuned ANS algorithmis, under Gaussian assumptions, statistically efficient, i.e. , it attains the Cram´er-Rao type lower smoothing bound, which limits accuracy of any frequency estimation scheme.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- ICASSP'08 [Dokument elektroniczny] : 2008 IEEE International Conference on Acoustics, Speech and Signal Processing : proceedings Las Vegas, Nevada, USA March 30-April 4, 2008. - Dane tekstowe. strony 3549 - 3552
- Language:
- English
- Publication year:
- 2008
- Bibliographic description:
- Niedźwiecki M.: From the multiple frequency tracker to the multiple frequency smoother// ICASSP'08 [Dokument elektroniczny] : 2008 IEEE International Conference on Acoustics, Speech and Signal Processing : proceedings Las Vegas, Nevada, USA March 30-April 4, 2008. - Dane tekstowe./ Las Vegas: IEEE, 2008, s.3549-3552
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/icassp.2008.4518418
- Verified by:
- Gdańsk University of Technology
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