Algorithms for instantaneous frequency estimation: a comparative study

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Algorithms for instantaneous frequency estimation: a comparative study

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dc.contributor.author Boashash, Boualem
dc.contributor.author O'Shea, Peter
dc.contributor.author Arnold, M.J.
dc.date.accessioned 2011-06-14T05:40:48Z
dc.date.available 2011-06-14T05:40:48Z
dc.date.issued 1990-07
dc.identifier.citation Proc. SPIE 1348, 126 (1990) en_US
dc.identifier.other doi:10.1117/12.23471
dc.identifier.uri http://hdl.handle.net/10576/10708
dc.description This was then work-in-progress to compare IF estimators. (The most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net). This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia., and then continuously updated). en_US
dc.description.abstract This paper examines the problem of instantaneous frequency (IF) estimation for Frequency Modulated (FM) signals imbedded in white Gaussian noise. It reviews currently available techniques and in addition proposes some new ones based on a modelling of the signal phase as a polynomial. Both linear least-squares techniques and Maximum Likelihood (ML) techniques are investigated for estimating the polynomial coefficients. It is seen that the linear least squares approach is efficient (i. e. unbiased and meets the Cramer-Rao bounds) for high SNR while the ML scheme is efficient for a much larger range of SNR. Theoretical lower variance bounds are given for estimating the polynomial coefficients and are compared with the results of simulations. Guidelines are given as to which estimation method should be used for a given signal class and Signal to Noise Ratio (SNR) level. en_US
dc.language.iso en en_US
dc.publisher SPIE en_US
dc.subject algorithms en_US
dc.subject computational efficiency en_US
dc.subject constant-amplitude phase-modulated signal en_US
dc.subject filtering en_US
dc.subject instantaneous frequency estimation en_US
dc.subject least squares methods en_US
dc.subject statistical efficiency en_US
dc.subject time-frequency analysis en_US
dc.subject time-frequency distributions en_US
dc.subject frequency tracking en_US
dc.subject Frequency estimation en_US
dc.subject Cramer–Rao Lower bound en_US
dc.subject phase difference estimator en_US
dc.subject zero-crossing en_US
dc.subject LMS en_US
dc.subject RLS en_US
dc.title Algorithms for instantaneous frequency estimation: a comparative study en_US
dc.type Article en_US

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