Abstract
Frequency Estimation methods have the ability to resolve complex exponentials that are closely spaced in frequency. The estimation of the frequencies is based on the eigen decomposition of the autocorrelation matrix of the input data. The autocorrelation matrix after eigen decomposition produces two subspaces, namely noise subspace and signal subspace. The methods that are based on the estimation of frequencies using noise subspace of the autocorrelation matrix are called Noise subspace methods of Frequency Estimation. Pisarenko Harmonic Decomposition, MUSIC method, Eigen Vector method and the Minimum Norm methods belongs to the category of Noise subspace methods. This paper investigates the performance evaluation of all the Noise Subspace methods of frequency estimation techniques for a common Synthetic Power signal having harmonics at 600Hz, 900Hz and 1500Hz with a sampling frequency of 3000Hz. Extensive Monte-Carlo simulation is carried out for ten numbers of times and the simulated figures are shown. The values obtained after the application of Noise subspace methods are compared with that of the actual inputs and are tabulated. The simulation of all methods is performed by using MATLAB software.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
References
Hayes, M.H.: Statistical Digital Signal Processing and Modeling. John Wiley & Sons, INC. (1996)
Proakis, J.G., Manolakis, D.G.: Digital Signal Processing Principles, Algorithms and Applications. PHI (2002)
Bollen, M.H.J., Gu, I.Y.H.: Signal Processing of Power Quality Disturbances. IEEE Press Series on Power Engineering (2011)
Kay, S., Marple Jr., S.L.: Sources and remedies for spectral line splitting in autoregressive spectrum analysis. In: Proc. Int. Conf. on Acoust, Speech, Sig. (1979)
Chapman, S.J.: MATLAB programming for Engineers. Thomson Pub., Toronto (2008)
Elliott, D.F.: Handbook of Digital Signal Processing Engineering Applications. Rockwell International Corporation Pub., Anaheim (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bramaramba, K., Koteswara Rao, S., Raja Rajeswari, K. (2012). Performance Evaluation of Noise Subspace Methods of Frequency Estimation Techniques. In: Satapathy, S.C., Avadhani, P.S., Abraham, A. (eds) Proceedings of the International Conference on Information Systems Design and Intelligent Applications 2012 (INDIA 2012) held in Visakhapatnam, India, January 2012. Advances in Intelligent and Soft Computing, vol 132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27443-5_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-27443-5_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27442-8
Online ISBN: 978-3-642-27443-5
eBook Packages: EngineeringEngineering (R0)