Scientific Production

SEARCH

Search

Conference Paper

Vers une carte d'identité spectrale

Authors: Martin Nadine, Mailhes Corinne, Sahli Kheira and Lejeune Gérard

In Proc. Groupement de Recherche en Traitement du Signal et des Images (GRETSI), September 6-9, 2005.

This paper studies a new spectral analysis strategy for detecting, characterizing and classifying the different “spectral st ructures” of an unknown stationary process. A “spectra l structure” is defined as a sinusoidal wave, a narrow band signal or a noise peak. The spectral analysis strategy is based on the use of several successive and complementary spect ral analyses. Then, the proposed methodology provides a way to calculate a “spectral identity card” of each spectral struct ure, similarly to a real I.D. card. This I.D. card including all information related to this structure results from th e fusion of intermediate cards, which are obtained from different spectral analysis al gorithms. The I.D. card permits the classification of the detected spectral structur e into one of the following four classes: Pure Frequency, Narr ow Band, Alarm and Reject.

Signal and image processing / Other

READ MORE

Amélioration de l'estimation spectrale par modélisation AR multi-dimensionnelle et découpage en sous-bandes

Authors: Bonacci David and Mailhes Corinne

In Proc. Groupement de Recherche en Traitement du Signal et des Images (GRETSI), September 6-9, 2005.

DOWNLOAD DOCUMENT

Subband decomposition has been shown to achieve very good performances for frequency estimation, particularly when parametric methods are used. This paper introduces a subband multichannel autoregressive spectral estimation method allowing to exploit the knowledge of intercorrelations between subseries in order to improve frequency estimation performances. This method is detailled then applied to a signals composed by a sum of 2 close sinusoids embedded in noise. Simulation results illustrate the interest of the proposed method.

Signal and image processing / Localization and navigation

READ MORE

Amélioration de l'estimation spectrale par modélisation AR multi-dimensionnelle et découpage en sous-bandes

Authors: Bonacci David and Mailhes Corinne

In Proc. Groupement de Recherche en Traitement du Signal et des Images (GRETSI), September 6-9, 2005.

DOWNLOAD DOCUMENT

Le découpage en sous-bandes est réputé pour ses très bonnes performances en matière d’estimation fréquentielle, en particulier lorsqu’on utilise des méthodes paramétriques. Cet article présente une méthode d’estimation spectrale basée sur le découpage en sous-bandes et la modélisation auto-regressive multi-dimensionnelle qui permet d’exploiter la connaissance des inter-corrélations entre les signaux de sousbande afin d’améliorer les performances de l’estimation fréquentielle. Le principe de la méthode est présenté puis appliquée à la résolution de 2 fréquences très proches dans le cas de signaux composés de deux fréquences pures très proches noyées dans du bruit. Des simulations effectuées sur des données synthétiques illustrent les performances de ce nouvel estimateur qui ouvre des perspectives intéressantes.

Signal and image processing / Other

READ MORE

Subband Decomposition Using Multichannel AR Spectral Estimation

Authors: Bonacci David, Mailhes Corinne and Castanié Francis

In Proc. IEEE Int. Conf. Acoust., Speech and Signal Processing (ICASSP), Philadelphia, USA, March 18-23, 2005.

DOWNLOAD DOCUMENT

Subband decomposition has been shown to be a useful tool for spectral estimation, in particular when parametric methods have to be considered. Indeed, the loss of observed samples due to decimation can be compensated by the use of a suitable model, if available. This paper studies a subband multichannel autoregressive spectral estimation (SMASE) method. The proposed method decomposes the observed signal through an appropriate filter bank and processes the decimated signals by means of a multichannel autoregressive (AR) model. This model takes advantage of known correlations between different subband signals. This a priori knowledge allows to improve spectral estimation performance. Simulation results illustrate the interest of the proposed methodology for signals with continuous spectra and for sinusoids.

Signal and image processing / Other

READ MORE

Improving High Resolution Spectral Analysis Methods for Radar Measurements Using Subband Decomposition

Authors: Bonacci David, Mailhes Corinne and Castanié Francis

In Proc. Int. Workshop on Intelligent Transportation (WIT), Hamburg, Germany, March 15-16, 2005.

DOWNLOAD DOCUMENT

This paper addresses the problem of spec-tral analysis on radar measurements using high res-olution methods. These methods have already been shown to yield better results than Fast Fourier Trans-form (FFT) based methods for accuracy on detected frequencies and more particularly for frequency res-olution. In most applications, these performances are closely related to the performances of range and veloc-ity estimation. In the paper, theoretical study shows the interest of subband decomposition for improving per-formances of frequency estimation in the case of the use of High Resolution methods, while it is shown to be inefficient when using FFT-based algorithms. Some elements of computational cost are given, in order to compare fullband and subband processing when using Fast Least Square Autoregressive (AR) algorithm. Fi-nally, experimental results are given, showing the inter-est of subband decomposition within the frame of radar signal processing either for accuracy and resolution on frequency estimation.

Signal and image processing / Localization and navigation

READ MORE

Comparison and Evaluation of Quality Criteria for Hyperspectral Imagery

Authors: Christophe Emmanuel, Leger Dominique and Mailhes Corinne

In Proc. SPIE Electronic Imaging, San Jose, USA, vol. 5668, pp. 204-213, January 17-20, 2005.

Hyperspectral data appears to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy. Handling the significant size of hyperspectral data presents a challenge for the user community. To enable efficient data compression without losing the potentiality of hyperspectral data, the notion of data quality is crucial for the development of applications. To assess the data quality, quality criteria relevent to end-user applications are required. This paper proposes a method to evaluate quality criteria. The purpose is to provide quality criteria corresponding well to the impact of degradation on end-user applications. Several quality criteria adapted to hyperspectral context are evaluated. Finally, five criteria are selected to give a good representation of the degradation nature and level affecting hyperspectral data.

Signal and image processing / Earth observation

READ MORE

The impact of High Resolution Spectral Analysis methods on the performance and design of millimetre wave FMCW radars

Authors: Bonacci David, Mailhes Corinne, Chabert Marie and Castanié Francis

In Proc. Int. Radar Conf. (Radar 2004), October 19-21, 2004.

DOWNLOAD DOCUMENT

This paper addresses the problem of joint measures of range and velocity of moving targets using millimetre wave FMCW radar (in the 77 Ghz range) within the field of automotive applications. The proposed solution is to determine range and velocity using spectral estimation of downconverted signals, theoretically composed of multiple sine functions embedded in noise. As a consequence, their accuracy is closely related to the accuracy of frequency estimation. In this paper, High Resolution spectral analysis methods (such as Auto-Regressive or Prony modeling) are shown to strongly impact the technological design constraints of the radars. More precisely, for a given sampling frequency of the downconverted signal, these methods show their ability either to significantly reduce the bandwidth of the linear frequency modulated radar sweeps although keeping constant the frequency resolution, or, for a given technological design, increase the same figure of merit. Moreover, adequate pre-processing of the signal is described, yielding correction of some 'nasty' non-linear effects (VCO, mixers, ...) as well as denoising received signals. Theoretical study of the performances is given and illustrated on simulated and real signals (provided by the RadarNet project of the 5th Framework Program).

Signal and image processing / Localization and navigation

READ MORE

PhD Thesis

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

Author: Bonacci David

Defended in December 2003

DOWNLOAD DOCUMENT

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

READ MORE

PhD Defense Slides

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

Author: Bonacci David

Defended in December 2003

DOWNLOAD DOCUMENT

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

READ MORE

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.

DOWNLOAD DOCUMENT

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

READ MORE

Activity Report

READ MORE

PhD positions available at TeSA

PhD subjects available on the CNES site.
On line application before the 1st of April.

READ MORE

Romain Chayot and Charles-Ugo Piat-Durozoi become Doctors

Congratulations!

Welcome to our new PhD students!

On this picture: Thomas, Vinicius and François (from left to right).