Polynomial Phase Estimation by Least Squares Phase Unwrapping

Estimating the coefficients of a noisy polynomial phase signal is important in fields including radar, biology and radio communications. One approach 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 must be...

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Bibliographic Details
Published in:	IEEE transactions on signal processing Vol. 62; no. 8; pp. 1962 - 1975
Main Authors:	McKilliam, Robby G., Quinn, Barry G., Clarkson, I. Vaughan L., Moran, Bill, Vellambi, Badri N.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 15.04.2014 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Applied sciences Asymptotic properties Computer simulation Detection, estimation, filtering, equalization, prediction Econometrics Economic models Estimating Estimators Exact sciences and technology Image processing Information, signal and communications theory Lattices Least squares approximations Least squares method nearest lattice point problem Phase estimation phase unwrapping polynomial phase signals Polynomials Radio communications Regression Signal and communications theory Signal processing Signal processing algorithms Signal to noise ratio Signal, noise Telecommunications and information theory Performance evaluation Monte Carlo method Parameter estimation State of the art Phase measurement Polynomial phase signal Phase unwrapping Image processing Asymptotic properties Theoretical study Image restoration Algorithm nearest lattice point problem polynomial phase signals Phase estimation Least squares method Radar Signal processing Numerical simulation Radio communication Polynomial regression Number theory
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
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