Please use this identifier to cite or link to this item:
Title: ML estimation of the frequency and phase in noise
Authors: Fu, H. 
Kam, P.Y. 
Keywords: CRLB
ML estimation
Phase noise model
Phase unwrapping
Issue Date: 2006
Citation: Fu, H.,Kam, P.Y. (2006). ML estimation of the frequency and phase in noise. GLOBECOM - IEEE Global Telecommunications Conference : -. ScholarBank@NUS Repository.
Abstract: The problem of estimating the frequency and carrier phase of a single sinusoid observed in additive, white, Gaussian noise is addressed. Much of the work in the literature considers maximum likelihood (ML) estimation. However, the ML estimator given by the location of the peak of a periodogram in the frequency domain [1] has a very high computational complexity. This paper derives an explicit structure of the ML estimator for data processing in the time domain, assuming only reasonably high signal-to-noise ratio. The result of this approximate ML estimator shows that both the phase and the magnitude of the noisy signal samples are utilized in the estimator, and the phase data alone as assumed in [2] and [3] is not a sufficient statistic. The sample-by-sample iterative processing nature of the estimator enables us to propose a novel, recursive phase-unwrapping algorithm that allows the estimator to be implemented efficiently. To facilitate the performance analysis, an improved, linearized observation model for the instantaneous signal phase that is more accurate than that of [2] and [3] is proposed. This improved model explains physically why the phase data are weighted by the magnitude information in the ML estimator. © 2006 IEEE.
Source Title: GLOBECOM - IEEE Global Telecommunications Conference
ISBN: 142440357X
DOI: 10.1109/GLOCOM.2006.581
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Jun 28, 2022

Page view(s)

checked on Jun 23, 2022

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.