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PhD Defense Slides

Intérêt du découpage en sous-bandes pour l'analyse spectrale

Author: Bonacci David

Defended in December 2003

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Subband decomposition has been successfully used in several applications in image and signal processing and telecommunication fields. It consists in presenting a signal at the input of a filterbank and then decimating (sampling rate decreasing) the obtained filtered signals. Some authors recently showed that it can be a powerful tool for spectral estimation, either for the classical one (based on the Fourier transform) or spectral estimation based on parametric modellings. The aim of this PhD is double: first, we present the motivations and drawbacks of parametric spectral estimation in the subbands and then we present several original methods able to take advantage of the good properties of subband decomposition while preventing some of its drawbacks. Particularly, some methods able to cancel spectral overlapping induced by sampling rate decreasing will be developped, as well as other methods permitting to increase the perfromances of spectral estimation using the intercorrelation between the sub-series descended from decimation.

Signal and image processing / Other

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Conference Paper

Improving Frequency Resolution for Correlation-Based Frequency Estimation Methods Using Subband Decomposition

Authors: Bonacci David, Mailhes Corinne and Djurić Petar M.

In Proc. Int. Conf. Acoust., Speech and Signal Processing (ICASSP), April 6-10, 2003.

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Subband decomposition has already been shown to increase the performance of spectral estimators, but induced frequency overlapping may be troublesome, bringing edge effects at subband borders. A recent paper (Bonacci, D. et al., EUSIPCO, 2002) proposed a method (SDFW - subband decomposition and frequency warping) allowing subband decomposition to be performed without aliasing. We modify this subband decomposition in order to improve frequency resolution for any correlation based spectral estimator when applied to the subband outputs. Three main improvements are proposed: the subband decomposition is based on comb filters; the SDFW method warping operation is performed using a complex frequency modulation; the autocorrelation is estimated using all sub-series from each subband. Simulation results demonstrate the anticipated performance of the proposed method.

Signal and image processing / Other

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Subband Decomposition and Frequency Warping for Spectral Estimation

Authors: Bonacci David, Michel Patrice and Mailhes Corinne

In Proc. European Signal and Image Processing Conference (EUSIPCO), Toulouse, France, September 3-6, 2002.

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Subband decomposition has already been shown to increase the performances of spectral estimation but induced frequency overlapping may be troublesome, bringing edge effects, when spectral estimation is applied after subband decomposition and decimation. This paper proposes a new spectral estimation procedure based on subband decomposition and frequency warping which reduces the overlapping frequency problem. Simulation results confirm the interest of this new algorithm.

Signal and image processing / Other

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Spectral Estimation Using Subband Decomposition and Frequency Warping

Authors: Bonacci David, Michel Patrice and Mailhes Corinne

In Proc. Int. Conf. Acoust., Speech and Signal Processing (ICASSP), Orlando, Florida, May 13-17, 2002.

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This paper addresses the problem of frequency overlapping which occurs when spectral estimation is applied after subband decomposition. Subband decomposition has already been shown to increase the performances of spectral estimation but induced frequency overlapping may be troublesome. This paper proposes a new spectral estimation procedure based on sub band decomposition and frequency warping which reduces the overlapping frequency problem. Simulations confirm the interest of this new algorithm.

Signal and image processing / Other

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A New Air Traffic Complexity Metric Based on Dynamical System Modelization

Authors: Delahaye Daniel, Paimblanc Philippe, Histon Jonathan M. and Hansman R. John

In Proceedings of the 21st IEEE Digital Avionics Systems Conference, Volume 1, pp 4A2-1 - 4A2-12

This paper presents new concepts to address the air traffic complexity modeling problem. Two new geometrical metrics have been introduced and have been found very useful to capture typical features of traffic complexity. The covariance metric is very adapted to identify disorder in a set of speed vectors and can be applied for en route airspace (en route airspace is the airspace between airports). Similarly, the Koenig metric identifies easily the curl movement organizations and can be applied to areas around airports where air traffic control procedures impose turns on aircraft trajectories.

Signal and image processing / Aeronautical communication systems and Localization and navigation

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Activity Report

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TeSA in Miami

Philippe Paimblanc, TeSA Researcher, Julien Lesouple and Lorenzo Ortega, TeSA PhD students, presented papers at ION GNSS+ 2018.

TeSA in Berlin

Bastien Tauran and Selma Zamoum, TeSA PhD students, presented papers at ASMS/SPSC 2018.

Yoann Couble becomes a Doctor

Congratulations!