Fast Tracking of a Real Sinusoid with Multiple Forgetting Factors

Authors:
Md. Tawfiq Amin;Kenneth Wing-Kin Lui;Hing-Cheung So
Affiliations:
-;-;-
Venue:
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Year:
2008

Citing 3
Cited 0

Digital spectral analysis: with applications

Digital spectral analysis: with applications
Fundamentals of statistical signal processing: estimation theory

Fundamentals of statistical signal processing: estimation theory
MAP/ML Estimation of the Frequency and Phase of a Single Sinusoid in Noise

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a recursive Gauss-Newton (RGN) algorithm is first developed for adaptive tracking of the amplitude, frequency and phase of a real sinusoid signal in additive white noise. The derived algorithm is then simplified for computational complexity reduction as well as improved with the use of multiple forgetting factor (MFF) technique to provide a flexible way of keeping track of the parameters with different rates. The effectiveness of the simplified MFF-RGN scheme in sinusoidal parameter tracking is demonstrated via computer simulations.