Smoothing of power spectral densities

Author

Hippenstiel, Ralph D.

Author_Institution

Dept. of Electr. & Comput. Eng., US Naval Postgraduate Sch., Monterey, CA, USA

fYear

1990

fDate

12-14 Aug 1990

Firstpage

1022

Abstract

Power spectral estimates are smoothed using a Kalman filtering approach. The filter is used to segment the power spectral density by separating signal-dominated regions from noise-dominated regions. In doing so, it tends to preserve the fidelity for signal-related spectral peaks while smoothing the segments dominated by the noise. Relative to standard windowing, noise contributions are reduced, while the resolution of an unwindowed spectral estimate is essentially preserved

Keywords

Kalman filters; filtering and prediction theory; Kalman filtering; noise-dominated regions; power spectral densities; signal-dominated regions; spectral density smoothing; spectral estimates; Filtering; Fourier transforms; Image edge detection; Image segmentation; Kalman filters; Noise level; Power engineering and energy; Power smoothing; Signal detection; Signal resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1990., Proceedings of the 33rd Midwest Symposium on

Conference_Location

Calgary, Alta.

Print_ISBN

0-7803-0081-5

Type

conf

DOI

10.1109/MWSCAS.1990.140898

Filename

140898

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2826453