DocumentCode
3397228
Title
Class 2 homomorphic estimation and detection of multiplicatively-combined signals
Author
Lindquist, Claude S. ; Awang, Mat Kamil
Author_Institution
Dept. of Electr. & Comput Eng., Miami Univ., Coral Gables, FL, USA
fYear
1991
fDate
14-17 May 1991
Firstpage
1090
Abstract
The authors discuss separating and detecting signals which are combined multiplicatively where the system input is the product of the signal and the noise or the unwanted component. This system can be applied to amplitude modulation, fading channels, audio dynamic range compression and expansion, automatic gain control, radar, sonar, image enhancement, and music applications. When either the model for the signal expectation spectrum or that for the noise expectation spectrum, but not both, is known a priori, the Class 2 algorithm has to be used. The unknown spectral model must be explicitly estimated a posteriori from the ideal filter input. Optimum estimation and detection filters are developed by using homomorphic techniques to separate these signals
Keywords
amplitude modulation; automatic gain control; fading; filtering and prediction theory; image processing; interference (signal); parameter estimation; radar; signal detection; sonar; AGC; Class 2 algorithm; Wiener type; amplitude modulation; audio dynamic range compression; automatic gain control; detection filters; dynamic range expansion; estimation filters; fading channels; homomorphic techniques; image enhancement; multiplicatively-combined signals; music applications; noise; noise expectation spectrum; optimum filters; radar; signal expectation spectrum; smoothing algorithm; sonar; spectral model; Amplitude modulation; Dynamic range; Fading; Filters; Gain control; Image coding; Radar applications; Radar detection; Radar imaging; Signal detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1991., Proceedings of the 34th Midwest Symposium on
Conference_Location
Monterey, CA
Print_ISBN
0-7803-0620-1
Type
conf
DOI
10.1109/MWSCAS.1991.251945
Filename
251945
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