NDLI: Estimation of Multicomponent Polynomial Phase Signals With Missing Observations

Content Provider	IEEE Xplore Digital Library
Author	Duc Son Pham Zoubir, A.M.
Copyright Year	1991
Abstract	In contrast to the assumption of perfect observations by a number of developed methods for the analysis of nonstationary signals, missing observations do occur in practice which lead to performance degradation. We consider the parameter estimation problem of multicomponent polynomial phase signals (PPS) when there are randomly missing observations. The derivation shows that the Cramer-Rao bound for the missing observations case can be readily obtained from the result of perfect observations. Then, we propose an expectation-maximization-based method to estimate the PPS parameters. Simulation results show that the proposed method approaches the Cramer-Rao bound at moderate to high signal-to-noise ratios whilst standard techniques fail when there is a fair amount of missing observations.
Sponsorship	IEEE Signal Processing Society
Starting Page	1710
Ending Page	1715
Page Count	6
File Size	1648409
File Format	PDF
ISSN	1053587X
Volume Number	56
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Phase estimation Polynomials Engines Signal analysis Signal processing Combustion Parameter estimation Sparks Ignition Monitoring polymonial phase signals CramÉr–Rao bound missing observations multicomponent nonlinear least squares nonlinear optimization
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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