M. CHALABI Izzeddine

Prof

Directory of teachers

Department

Departement of ELECTRONICS

Research Interests

Specialized in Departement of ELECTRONICS. Focused on academic and scientific development.

Contact Info

University of M'Sila, Algeria

Email : izzeddine.chalabi@univ-msila.dz

On the Web:

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Recent Publications

2024-10-09

Sea Clutter Modelling using Compound Gaussian with Nakagami Texture plus Thermal Noise

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

M. CHALABI Izzeddine, (2024-10-09), "Sea Clutter Modelling using Compound Gaussian with Nakagami Texture plus Thermal Noise", [national] PRZEGLĄD ELEKTROTECHNICZNY , SEP – Polish Electrical Engineers Association (SEP)

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2024-07-19

Fractional Order Moment Parameter Estimator of Compound-Gaussian Clutter with Nakagami-Distributed Textures

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

M. CHALABI Izzeddine, (2024-07-19), "Fractional Order Moment Parameter Estimator of Compound-Gaussian Clutter with Nakagami-Distributed Textures", [international] 12th International Conference On Applied Analysis And Mathematical Modeling (ICAAMM24), 2024, Istambul, Turkey , Turkey

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2024-07-09

Fractional Negative Order Moment Parameter Estimator of Compound-Gaussian Clutter with Lognormal Texture

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

M. CHALABI Izzeddine, (2024-07-09), "Fractional Negative Order Moment Parameter Estimator of Compound-Gaussian Clutter with Lognormal Texture", [national] PRZEGLĄD ELEKTROTECHNICZNY , SEP – Polish Electrical Engineers Association (SEP)

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2023-11-23

performance analysis of CFAR detectors in pareto clutter

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

M. CHALABI Izzeddine, Amir Benzaoui, , (2023-11-23), "performance analysis of CFAR detectors in pareto clutter", [international] the 1st edition of the international conference on electronics engineering and telecommunications , Bordj Bou Arreridj university , Algeria

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2023-11-22

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

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

M. CHALABI Izzeddine, (2023-11-22), "Performance Analysis of coherent detection in Compound-Gaussian Clutter with Inverse Rayleigh Texture", [international] International Conference on Electronics Engineering and Telecommunications (2ETA2023). , University of Bordj Bou Arreridj, Algeria

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Performance analysis of CFAR detectors in pareto clutter

Performance analysis of CFAR detectors in pareto clutter.
Citation

M. CHALABI Izzeddine, (2023-11-22), "Performance analysis of CFAR detectors in pareto clutter", [international] International Conference on Electronics Engineering and Telecommunications (2ETA2023). , University of Bordj Bou Arreridj, Algeria

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

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

M. CHALABI Izzeddine, (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] International Conference on Electronics Engineering and Telecommunications (2ETA2023). , University of Bordj Bou Arreridj, Algeria

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2023-07-10

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

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

M. CHALABI Izzeddine, (2023-07-10), "Comparative Study of non-Gaussian Radar Clutter Modelling Using Compound Models.", [international] International conference on nonlinear science and complexity , Istambul, Turkey

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2023-05-23

High-resolution sea clutter modelling using compound inverted exponentiated Rayleigh distribution

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

M. CHALABI Izzeddine, (2023-05-23), "High-resolution sea clutter modelling using compound inverted exponentiated Rayleigh distribution", [national] Remote Sensing Letters , Taylor & Francis

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