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Random process reconstruction from multiple noisy source observations

Lacaze, Bernard and Mailhes, Corinne Random process reconstruction from multiple noisy source observations. (2004) Sampling Theory in Signal and Image Processing, vol. 3 (n°3). pp. 257-277. ISSN 1530-6429

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Official URL: http://stsip.org/vol03/no3/vol03no3pp257-277.html

Abstract

The problem addressed in this paper is the reconstruction of a continuous-time stationary random process from noisy sampled observations coming from different sources. An optimal solution in terms of linear filtering of observed samples is derived and the expression of the corresponding minimum reconstruction error power is given. Moreover, two equivalent reconstruction schemes are given. The first one is recursive, involving two filter banks. Its main interest is that adding or suppressing an input does not affect the whole scheme. The second scheme is symmetric and uses only one filter bank. However, to add a new input requires a complete modification of all the filter transfer functions. Simulation examples are given to prove the application of the reconstruction scheme

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National des Etudes Spatiales - CNES
French research institutions > Centre National de la Recherche Scientifique - CNRS
Université de Toulouse > Ecole Nationale de l'Aviation Civile - ENAC
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT
Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE
Other partners > Rockwell Collins (FRANCE)
Other partners > Thales (FRANCE)
Other partners > Telecom ParisTech (FRANCE)
Université de Toulouse > Université Paul Sabatier-Toulouse III - UPS
Université de Toulouse > Université de Toulouse II-Le Mirail - UTM
Université de Toulouse > Université de Toulouse I-Sciences Sociales - UT1
Other partners > Direction Générale de l’Aviation Civile - DGAC (FRANCE)
Laboratory name:
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Deposited By: Corinne MAILHES

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