IZZEDDINE Chalabi

Abdelkarim Mostafa

Performance Analysis of non-Gaussian Sea Clutter Modelling Using Compound Inverse Exponentiated Rayleigh Distribution.

Hafidi Salaheddine , Drif Nour el Islam

Détection des mauvaises herbes dans un champ agricole en utilisant l’apprentissage machine

DJOUDI Wiam , LOUANAS Imane

Analyse de performance de la détection CFAR dans un clutter non-homogène de distribution Gamma.

BOUNAB Asma , HADJAB Chyema

Etude et dimensionnement d’un réseau de communication mobile.

MERZEUGUI Seussane

Estimation des paramètres du clutter CG-LNT en présence du bruit thermique.

BELAMRI Fatima , SAOUDI Baha Eddine

Analyse de performance du détecteur TGM-CFAR dans un clutter non-homogène de distribution Pareto.

ACHOUR Asma , MERZOUG Safia

Modélisation des échos radar par la loi Gaussienne composée avec la texture log-normal en absence et en présence du bruit thermique.

Sea clutter modelling is crucial issue for constant false alarm rate (CFAR) radar detection. Several works had shown that sea clutter has a non-Gaussian nature. several heavy-tailed distributions have been proposed to model the sea clutter such as compound K (Ck), compound inverse Gaussian (CIG) and compound inverted exponentiated Rayleigh distribution (CIER). Recently, a new compound model has introduced by using Nakagami-distributed texture (CGNG) to model sea clutter with high-resolution at medium/high grazing angles. In this manuscript, we propose to extend the CGNG distribution to cover the presence of additive thermal noise and show the modelling performance using high resolution sea clutter data.

Citation

IZZEDDINE Chalabi , , (2024-10-09), Sea Clutter Modelling using Compound Gaussian with Nakagami Texture plus Thermal Noise, PRZEGLĄD ELEKTROTECHNICZNY, Vol:2024, Issue:10, pages:5, SEP – Polish Electrical Engineers Association (SEP)

This paper deals with parameter estimation of Compound-Gaussian Clutter with Nakagami-Distributed Textures (CGNG). CGNG was recently proposed to model sea clutter at medium/high grazing angles, where the parameters were estimated using the higher order moments estimator (HOME) and [zlog(z)] method. In order to improve the estimation performance, the fractional order moment estimator (FOME) is proposed in this paper. The obtained results show that the proposed FOME estimator provides the best estimation accuracy comparing to the HOME and the [zlog(z)] methods using both simulated and real data.

Citation

IZZEDDINE Chalabi , ,(2024-07-19), Fractional Order Moment Parameter Estimator of Compound-Gaussian Clutter with Nakagami-Distributed Textures,12th International Conference On Applied Analysis And Mathematical Modeling (ICAAMM24), 2024, Istambul, Turkey,Turkey

parameter estimation of Compound-Gaussian with lognormal texture (CG-LNT) distribution is considered. The CG-LNT distribution is nonGaussian heavy-tailed distribution, it used in radar domain to describe the variation of high-resolution sea clutter. The probability density function (PDF) is characterized by two parameters, the standard deviation and the mean. This paper proposes a closed form estimator of CG-LNT distribution parameters based on fractional negative order moment (FNOME). Comparative study is established against the existing estimators existing in the literature to evaluate the efficiency of the proposed estimator using CG-LNT simulated and real sea clutter data, the mean square error (MSE) criterion is also used to measure the estimation accuracy.

Citation

zoulikha douiou , IZZEDDINE Chalabi , ABDELKADER DJERAD , , (2024-07-09), Fractional Negative Order Moment Parameter Estimator of Compound-Gaussian Clutter with Lognormal Texture, PRZEGLĄD ELEKTROTECHNICZNY, Vol:100, Issue:7, pages:42-45, SEP – Polish Electrical Engineers Association (SEP)

CFAR (Constant false alarm rate) detection is a procedure that can be implemented in radars. Today, radars cover a wide range of disciplines in various fields such as aeronautics, military, meteorology, automobile traffic, etc. In this context, the aim of this paper is to analyze the performance of the TM-CFAR (Trimmed mean), GM-CFAR (Geometric mean) and OS-CFAR (Order statistic) detectors in Pareto distributed clutter. Comparative study has been carried out using the previous detectors for different situations including homogeneous and heterogeneous clutter.

Citation

Maroua LOUGLAIB , IZZEDDINE Chalabi , Amir Benzaoui, ,(2023-11-23), performance analysis of CFAR detectors in pareto clutter,the 1st edition of the international conference on electronics engineering and telecommunications,Bordj Bou Arreridj university , Algeria

Performance analysis of parameter estimation for compound Gaussian with log-normal texture clutter in the presence and absence of thermal noise

Citation

IZZEDDINE Chalabi , ,(2023-11-22), Performance analysis of parameter estimation for compound Gaussian with log-normal texture clutter in the presence and absence of thermal noise,International Conference on Electronics Engineering and Telecommunications (2ETA2023).,University of Bordj Bou Arreridj, Algeria

Performance analysis of CFAR detectors in pareto clutter.

Citation

IZZEDDINE Chalabi , ,(2023-11-22), Performance analysis of CFAR detectors in pareto clutter,International Conference on Electronics Engineering and Telecommunications (2ETA2023).,University of Bordj Bou Arreridj, Algeria

Performance Analysis of coherent detection in Compound-Gaussian Clutter with Inverse Rayleigh Texture.

Citation

IZZEDDINE Chalabi , ,(2023-11-22), Performance Analysis of coherent detection in Compound-Gaussian Clutter with Inverse Rayleigh Texture,International Conference on Electronics Engineering and Telecommunications (2ETA2023).,University of Bordj Bou Arreridj, Algeria

Comparative Study of non-Gaussian Radar Clutter Modelling Using Compound Models.

Citation

IZZEDDINE Chalabi , ,(2023-07-10), Comparative Study of non-Gaussian Radar Clutter Modelling Using Compound Models.,International conference on nonlinear science and complexity,Istambul, Turkey

This letter addresses high-resolution sea clutter modelling. Radar clutter modelling is essential to develop constant false alarm rate (CFAR) detection schemes. In this paper, we propose a compound model by the use of the inverted exponentiated Rayleigh (IER) distribution as texture component. The probability density function (PDF) of the compound inverted exponentiated Rayleigh (CIER) distribution is a function of three parameters including the thermal noise power. To assess the modelling performance of the CIER distribution, several tests have been performed using the Intelligent PIXel Processing Radar (IPIX) database where the fitted PDFs and the complimentary cumulative density functions (CCDFs) of the CIER, the well-known compound K and the compound inverse Gaussian (CIG) distributions are compared with the real PDF and CCDF. The results obtained validate the ability of the CIER distribution to model high-resolution sea clutter.

Citation

IZZEDDINE Chalabi , , (2023-05-23), High-resolution sea clutter modelling using compound inverted exponentiated Rayleigh distribution, Remote Sensing Letters, Vol:15, Issue:5, pages:433-441, Taylor & Francis