Adaptive Comb Filtering for Harmonic Signal Enhancement

Arye Nehorai, Boaz Porat

Research output: Contribution to journalArticlepeer-review

214 Scopus citations

Abstract

A new algorithm is presented for adaptive comb filtering and parametric spectral estimation of harmonic signals with additive white noise. The algorithm is composed of two cascaded parts. The first estimates the fundamental frequency and enhances the harmonic component in the input, and the second estimates the harmonic amplitudes and phases. Performance analysis provides new results for the asymptotic Cramer-Rao bound (CRB) on the parameters of harmonic signals with additive white noise. Results of simulations indicate that the variances of the estimates are of the same order of magnitude as the CRB for sufficiently large data sets, and illustrate the performance in enhancing noisy artificial periodic signals.

Original languageEnglish
Pages (from-to)1124-1138
Number of pages15
JournalIEEE Transactions on Acoustics, Speech, and Signal Processing
Volume34
Issue number5
DOIs
StatePublished - Oct 1986

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