Parameter estimation of superimposed sinusoids by data matrix subfactorization: Analysis and results > International Conferences

Parameter estimation of superimposed sinusoids by data matrix subfactorization: Analysis and results
Year	2016
Month
Journal	2016 / International Conference on Actual Problems of Electron Devices Engineering (APEDE)
Author	Artem Muchkaev, Seung-Hyun Kong*, Alexey L'vov
Link	https://ieeexplore.ieee.org/document/7879043 869회 연결
Estimating parameters of a sum of complex exponentials in white noise is considered in this paper. A simplified maximum likelihood estimation algorithm based on subfactorization of a structured data matrix is proposed, and we show that parameterization of the data model in signal space allows to improve estimation accuracy at low signal-to noise ratio (SNR). Basing on the proposed algorithm the computer simulation of the numerical example is accomplished. It is shown that the acheived accuracy is slightly less than the accuracy of efficient estimate corresponding to the low Cramer-Rao bound.