Title :
Smoothing of power spectral densities
Author :
Hippenstiel, Ralph D.
Author_Institution :
Dept. of Electr. & Comput. Eng., US Naval Postgraduate Sch., Monterey, CA, USA
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;
Conference_Titel :
Circuits and Systems, 1990., Proceedings of the 33rd Midwest Symposium on
Conference_Location :
Calgary, Alta.
Print_ISBN :
0-7803-0081-5
DOI :
10.1109/MWSCAS.1990.140898
