The asymptotic properties of polynomial phase estimation by least squares phase unwrapping

Robby G. McKilliam*, I. Vaughan L Clarkson, Barry G. Quinn, Bill Moran

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

    4 Citations (Scopus)

    Abstract

    Estimating the coefficients of a noisy polynomial phase signal is important in many fields including radar, biology and radio communications. One approach to estimation attempts to perform polynomial regression on the phase of the signal. This is complicated by the fact that the phase is wrapped modulo 2π and therefore must be unwrapped before the regression can be performed. A recent approach suggested by the authors is to perform the unwrapping in a least squares manner. It was shown by Monte Carlo simulation that this produces a remarkably accurate estimator. In this paper we describe the asymptotic properties of this estimator, showing that it is strongly consistent and deriving its central limit theorem. We hypothesise that the estimator produces very near maximum likelihood performance.

    Original languageEnglish
    Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
    Place of PublicationPiscataway, N.J.
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages3592-3595
    Number of pages4
    ISBN (Electronic)9781457705397
    ISBN (Print)9781457705380
    DOIs
    Publication statusPublished - 2011
    Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
    Duration: 22 May 201127 May 2011

    Other

    Other36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
    CountryCzech Republic
    CityPrague
    Period22/05/1127/05/11

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