Abdel Boudraa

Ecole Navale, Signal and Acosutics, Faculty Member

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Papers by Abdel Boudraa

An improved image demodulation algorithm based on Teager-Kaiser operator

HAL (Le Centre pour la Communication Scientifique Directe), 2008

Emd-Based Signal Noise Reduction

This paper introduces a new signal denoising based on the Empirical mode decomposition (EMD) fram... more This paper introduces a new signal denoising based on the Empirical mode decomposition (EMD) framework. The method is a fully data driven approach. Noisy signal is decomposed adaptively into oscillatory components called Intrinsic mode functions (IMFs) by means of a process called sifting. The EMD denoising involves filtering or thresholding each IMF and reconstructs the estimated signal using the processed IMFs. The EMD can be combined with a filtering approach or with nonlinear transformation. In this work the Savitzky-Golay filter and shoftthresholding are investigated. For thresholding, IMF samples are shrinked or scaled below a threshold value. The standard deviation of the noise is estimated for every IMF. The threshold is derived for the Gaussian white noise. The method is tested on simulated and real data and compared with averaging, median and wavelet approaches.

Ship detection and tracking from single ocean-bottom seismic and hydroacoustic stations

The Journal of the Acoustical Society of America

We report in this study how ocean-bottom seismometers (OBS) can be used as passive sonars to auto... more We report in this study how ocean-bottom seismometers (OBS) can be used as passive sonars to automatically detect, localize, and track moving acoustic sources at the ocean surface. We developed single-station methods based on direction of arrival and on multi-path interference measurements capable of handling continuous erratic signals emitted by ships. Based on a Bayesian mathematical framework, we developed an azimuthal detector and a radial detector and combined them into a fully automatic tracker. We tested the developed algorithm on seismic and hydroacoustic data recorded in the Indian Ocean by an OBS deployed at 4300 m depth, 200 km west of La Réunion Island. We quantified the performances using archives of commercial-vessel trajectories in the area provided by the Automatic Identification System. Detectors demonstrate capabilities in the detection range up to 100 km from the OBS with azimuthal accuracies of a few degrees and with distance accuracies of a few hundred of meters...

Analyse des signaux AM-FM basée sur une version B-splines de l'EMD-ESA

In this paper a signal analysis framework for estimating time-varying amplitude and frequency fun... more In this paper a signal analysis framework for estimating time-varying amplitude and frequency functions of multicomponent amplitude and frequency modulated (AM–FM) signals is introduced. This framework is based on local and non-linear approaches, namely Energy Separation Algorithm (ESA) and Empirical Mode Decomposition (EMD). Conjunction of Discrete ESA (DESA) and EMD is called EMD–DESA. A new modified version of EMD where smoothing instead of an interpolation to construct the upper and lower envelopes of the signal is introduced. Since extracted IMFs are represented in terms of B-spline (BS) expansions, a closed formula of ESA robust against noise is used. Instantaneous Frequency (IF) and Instantaneous Amplitude (IA) estimates of a multi- component AM–FM signal, corrupted with additive white Gaussian noise of varying SNRs, are analyzed and results compared to ESA, DESA and Hilbert transform-based algorithms. SNR and MSE are used as figures of merit. Regularized BS version of EMD– E...

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HLS-based Accelerated Simulation of Large Scale Cyber-Physical Systems on FPGAs

2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)

The design of cyber-physical systems remains challenging because of their highly heterogeneous na... more The design of cyber-physical systems remains challenging because of their highly heterogeneous nature that makes modeling, design and analysis hard. Despite extensive work in model-based approaches, few unified simulation tools are available today for such systems. This paper proposes a simulation strategy that benefits from the characteristics of recent FPGA platforms and advances in the high-level synthesis tools. Our proposal consists in using these tools to build a cyber-physical system simulator running at high-speed on a FPGA; in this view, high-level synthesis is used not only in the traditional prototyping phase of the embedded systems, but also to synthesize its physical environment, which is jointly simulated on the FPGA. Our paper proposes a case study illustrating this approach: the simulation of the automatic identification system required in maritime communications. The simulation executed on the latest FPGA generation is accelerated by a factor x654 compared to software alternatives demonstrating that FPGAs exhibit appealing characteristics for such simulations.

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Some useful properties of Cross-Psi_B-Energy Operator

WOSInternational audienc

Graph signals classification using total variation and graph energy informations

2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

In this work, we consider the problem of graph signals classification. We investigate the relevan... more In this work, we consider the problem of graph signals classification. We investigate the relevance of two attributes, namely the total variation (TV) and the graph energy (GE) for graph signals classification. The TV is a compact and informative attribute for efficient graph discrimination. The GE information is used to quantify the complexity of the graph structure which is a pertinent information. Based on these two attributes, three similarity measures are introduced. Key of these measures is their low complexity. The effectiveness of these similarity measures are illustrated on five data sets and the results compared to those of five kernel-based methods of the literature. We report results on computation runtime and classification accuracy on graph benchmark data sets. The obtained results confirm the effectiveness of the proposed methods in terms of CPU runtime and of classification accuracy. These findings also show the potential of TV and GE informations for graph signals classification.

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Audio coding via EMD

Digital Signal Processing, 2020

In this paper an audio coding scheme based on the empirical mode decomposition in association wit... more In this paper an audio coding scheme based on the empirical mode decomposition in association with a psychoacoustic model is presented. The principle of the method consists in breaking down adaptively the audio signal into intrinsic oscillatory components, called Intrinsic Mode Functions (IMFs), that are fully described by their local extrema. These extrema are encoded. The coding is carried out frame by frame and no assumption is made upon the signal to be coded. The number of allocated bits varies from mode to mode and obeys to the coding error inaudibility constraint. Due to the symmetry of an IMF, only the extrema (maxima or minima) of one of its interpolating envelopes are perceptually coded. In addition, to deal with rapidly changing audio signals, a stationarity index is used and when a transient is detected, the frame is split into two overlapping sub-frames. At the decoder side, the IMFs are recovered using the associated coded maxima, and the original signal is reconstructed by IMFs summation. Performance of the proposed coding is analyzed and compared to that of MP3 and AAC codecs, and the wavelet-based coding approach. Based on the analyzed mono audio signals, the obtained results show that the proposed coding scheme outperforms the MP3 and the wavelet-based coding methods and performs slightly better than the AAC codec, showing thus the

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Empirical Mode Decomposition and some operators to estimate Instantaneous Frequency: A comparative study

2008 3rd International Symposium on Communications, Control and Signal Processing, 2008

The aim of the present work is to illustrate how the empirical mode decomposition (EMD) can be as... more The aim of the present work is to illustrate how the empirical mode decomposition (EMD) can be associated with demodulation methods to estimate the instantaneous frequency (IF) of multicomponent non stationary signals. The IF estimation of three methods, namely, Hilbert-Huang transform (HHT) [10], EMD-DESA (Discrete Energy Separation Algorithm)also known as Teager-Huang transform (THT) [2] [5], and B-spline version of the

Seuillage d'images basé sur l'opérateur de Teager-Kaiser

-Le seuillage de l'histogramme d'une image est une procédure classique de segmentation. Dans ce t... more -Le seuillage de l'histogramme d'une image est une procédure classique de segmentation. Dans ce travail, on s'intéresse au problème du seuillage d'images en deux niveaux, pour extraire une information binaire pertinente. On propose une nouvelle méthode de seuillage qui inclut l'information contextuelle du pixel, en utilisant les contours pour estimer le seuil. Plus exactement, au lieu d'utiliser un détecteur de contours classique, on utilise l'Opérateur d'Énergie de Teager-Kaiser (OETK) pour mesurer l'activité enénergie du pixel. En effet, cet opérateur reflète mieux l'activité enénergie du pixel qu'un détecteur de contours classique (Laplacien,...). Les résultats obtenus sur des images synthétiques et réelles montrent l'intérêt de l'attribut du contexte. La comparaison avec les méthodes d'Otsu et de Kitler montrent l'apport de l'OETKà l'estimation du seuil.

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Estimation de la fréquence instantanée dun signal multi-composante par décomposition modale empirique et une version B-splines de lopérateur dénergie de Teager-Kaiser

Teager–Kaiser energy methods for signal and image analysis: A review

Digital Signal Processing, 2018

This paper provides a review of the Teager-Kaiser (TK) energy operator and its extensions for sig... more This paper provides a review of the Teager-Kaiser (TK) energy operator and its extensions for signals and images processing. This class of operators possesses simplicity and good time-resolution and is very efficient in instantaneously estimating AM-FM signals and images. We point out the importance of the concept of energy from the point of view of the generation of the signal. More precisely, we emphasize the importance of analyzing signals from the point of view of the energy of the system needed to produce them. We show how this class of TK energy operators can be used to estimate useful features for signals and images analysis in time, space and frequency domains such as instantaneous frequency, second-order moment frequency, coherence function or spatial envelope and phase. We also show the importance of the higher derivative order of TK energy operator in terms of demodulation for both mono and multi-dimensional signals. Most of the developed tools around TK energy operators deal with real and complex-valued signals and some of them extended to multi-dimensional case. Due to their low complexity and their instantaneous-adapting nature, the class of TK energy operators offers valuable processing tools for time (space), frequency and time-frequency analysis.

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Performance Optimization of Underwater Communication Links at Different Ranges for AIS Relay to AUV

Applied Sciences

Autonomous Underwater Vehicles (AUVs) are becoming increasingly popular for large number of civil... more Autonomous Underwater Vehicles (AUVs) are becoming increasingly popular for large number of civil and military applications, such as environmental monitoring, oceanography, archaeology, or mine warfare. Operational safety issue still prevents the exploitation of the full potential of AUVs. Operations of AUVs are limited by constraints including the need to guarantee no collision with manned surface vehicles. To avoid collisions, a solution is to relay surface vessel positions to the AUVs by an underwater communication link. The communication must be optimized to establish a robust and reliable link at various range and depth. Commercial underwater acoustic modems are often dedicated for specific distances and bit rates with performances strongly dependent on the environmental conditions. For the considered application, the modem must be adaptive at the time and frequency selectivity of the channel which is varying according to the operation context. In this work, we propose an adapt...

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A Data Extraction Method for Anomaly Detection in Naval Systems

2020 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2020

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Antarctic Blue Whale calls detection based on an improved version of the stochastic matched filter

2017 25th European Signal Processing Conference (EUSIPCO), 2017

As a first step to Antarctic Blue Whale monitoring, a new method based on a passive application o... more As a first step to Antarctic Blue Whale monitoring, a new method based on a passive application of the Stochastic Matched Filter (SMF) is developed. To perform Z-call detection in noisy environment, improvements on the classical SMF requirements are proposed. The signal's reference is adjusted, the background noise estimation is reevaluated to avoid operator's selection, and the time-dependent Signal to Noise Ratio (SNR) estimation is revised by time-frequency analysis. To highlight the SMF's robustness against noise, it is applied on a Ocean Bottom Seismometers hydrophone-recorded data and compared to the classical Matched Filter: the output's SNR is maximized and the false alarm drastically decreased.

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Experimental Investigation of Wall-pressure Fluctuations On a Transiently Moving Hydrofoil By Empirical Mode Decomposition

Ce travail présente une étude expérimentale du champ de pression pariétale sur un corps portant e... more Ce travail présente une étude expérimentale du champ de pression pariétale sur un corps portant en mouvement de rotation transitoire de grande amplitude. Les signaux obtenus sont instationnaires, turbulent, large bande, bruités et incluent différentes caractéristiques de l'écoulement apparaissant au cours du mouvement transitoire. Dans ce cadre l'analyse des signaux de pression a été réalisée à l'aide d'une technique de décomposition modale empirique (EMD) adaptée aux signaux transitoires qui décompose le signal en bandes de fréquences sur la base de fonctions modales intrinsèques (IMFs). La méthode sépare ainsi les composantes hautes fréquences des composantes basses fréquences intrinsèques au signal étudié. Outre le bruit haute fréquence elle permet de distinguer un certain nombre de caractéristiques de l'écoulement comme la transition laminaire-turbulent caractérisé par l'apparition de composantes hautes -fréquences au cours du mouvement basse fréquence de rotation. Sur la base d'un développement sur les modes basses fréquences, on observe que la transition se déplace au cours du mouvement de rotation jusqu'au décollement de bord d'attaque caractérisé par un fort pic de pression suivi d'oscillations basses fréquences.

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EMD-Based Filtering Using Similarity Measure Between Probability Density Functions of IMFs

IEEE Transactions on Instrumentation and Measurement, 2014

This paper introduces a new signal-filtering, which combines the empirical mode decomposition (EM... more This paper introduces a new signal-filtering, which combines the empirical mode decomposition (EMD) and a similarity measure. A noisy signal is adaptively broken down into oscillatory components called intrinsic mode functions by EMD followed by an estimation of the probability density function (pdf) of each extracted mode. The key idea of this paper is to make use of partial reconstruction, the relevant modes being selected on the basis of a striking similarity between the pdf of the input signal and that of each mode. Different similarity measures are investigated and compared. The obtained results, on simulated and real signals, show the effectiveness of the pdf-based filtering strategy for removing both white Gaussian and colored noises and demonstrate its superior performance over partial reconstruction approaches reported in the literature.

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Analysis of Intrinsic Mode Functions: A PDE Approach

IEEE Signal Processing Letters, 2010

The empirical mode decomposition is a powerful tool for signal processing. Because of its origina... more The empirical mode decomposition is a powerful tool for signal processing. Because of its original algorithmic, recent works have contributed to its theoretical framework. Following these works, some mathematical contributions on its comprehension and formalism are provided. In this paper, the so called local mean is computed in such a way that it allows the use of differential calculus on envelopes. This new formulation makes us prove that iterations of the sifting process are well approximated by the resolution of partial differential equations (PDE). Intrinsic mode functions are originally defined in a intuitive way. Herein, a mathematical characterization of modes is given with the proposed PDEbased approach.

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Audio encoding based on the Empirical Mode Decomposition

2009 17th European Signal Processing Conference, 2009

This paper deals with a new approach for perceptual audio encoding, based on the Empirical Mode D... more This paper deals with a new approach for perceptual audio encoding, based on the Empirical Mode Decomposition (EMD). The audio signal is decomposed adaptively into intrinsic oscillatory components by EMD called Intrinsic Mode Functions (IMFs), which can be fully described by their extrema. These extrema are encoded after an appropriate thresholding scheme controlled by a psycho-acoustic model. The decoder recovers the original signal after IMFs reconstruction by means of spline interpolation and their summation. The proposed approach is applied to different audio signals and results are compared to wavelets and to MPEG1-layer3 (MP3) approaches. Relying on exhaustive simulations, the obtained results show that the proposed compression scheme performs better than the MP3 and the wavelet approach in terms of bit rate and audio quality.

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A new class of multi-dimensional Teager-Kaiser and higher order operators based on directional derivatives

Multidimensional Systems and Signal Processing, 2012

This work aims at introducing some energy operators linked to Teager-Kaiser energy operator (Kais... more This work aims at introducing some energy operators linked to Teager-Kaiser energy operator (Kaiser, 1990) and its associated higher order versions and expand them to multidimensional signals. These operators are very useful for analyzing oscillatory signals with time-varying amplitude and frequency (AM-FM). We prove that gradient tensors combined with Kronecker powers allow to express these operators by directional derivatives along any n-D vector. In particular, we show that the construction of a large class of non linear operators for AM-FM multidimensional signal demodulation is possible. Also, a new scalar function using the directional derivative along a vector giving the "sign" of the frequency components is introduced. An application of this model to local n-D AM-FM signal is presented and related demodulation error rates estimates. To show the effectiveness and the robustness of our method in term of envelope and frequency components extraction, results obtained on synthetic and real data are compared to multi-dimensional energy separation algorithm (Maragos and Bovik, 1995) and to our recently introduced n-D operator (Salzenstein and Boudraa, 2009).

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