AHMED Bentoumi
أحمد بن التومي
ahmed.bentoumi@univ-msila.dz
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- MI - Joint Basci Teaching Department
- Faculty of Mathematics and Informatics
- Grade PHd
About Me
Location
Msila, Msila
Msila, ALGERIA
Code RFIDE- 2020-02-11 00:00:00
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AHMED Bentoumi birthday
- 2020
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2020
Parameter Estimation of Rayleigh-Generalized Gamma Mixture Model
The estimation problem of three parameters Rayleigh-Generalized Gamma Mixture (R-GG) radar clutter model is addressed in this paper. Expressions of integer order moments, non-integer order moments and logarithmic moments are presented in such away the scale parameter of the R-GG probability density function (PDF) is eliminated and a two-dimensional estimators labeled HOME, NIOME and [zlog(z)] methods are obtained. Due to the presence of gamma function with fractional variables, these estimators cannot be given in closed forms. The fitness function for each estimator is given as a sum of squared errors of nonlinear equations. Using a numerical routine based upon the simplex search algorithm, the proposed methods were tested firstly on artificial data. Tail fitting of the R-GG model and the standard K-distribution (i.e., special case of the R-GG) is assessed against recorded radar data. The accuracy of the R-GG model and the proposed estimation methods is satisfactory, with the most accuracy of the [zlog(z)] method.
Citation
Ahmed BENTOUMI , AMAR Mezache , Houcine OUDIRA , , (2020), Parameter Estimation of Rayleigh-Generalized Gamma Mixture Model, Instrumentation Mesure Métrologie, Vol:19, Issue:1, pages:59-64, IIETA
- 2019
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2019
Model Selection of Sea Clutter Using Cross Validation Method
This work concerns a model selection of sea radar clutter used for adaptive target detection. Three distributions without thermal noise are considered; K, Pareto type II and compound Gaussian inverse Gaussian (CG-IG) with scale and shape parameters. The model selection is carried out by comparing the experimental complementary cumulative distribution function (CCDF), drawn from the recorded data intensity, to a set of the CCDF curves derived from the underling models. To do this, the cross validation technique is used after dividing a set of data into four segments. The best distribution is selected in which the mean of the means square of errors (MSEs) between the real CCDF curve and the fitted CCDF curve is minimal. Fitting comparisons of models are illustrated through overall data of Intelligent PIxel X-band radar (IPIX). From this study, it is shown that the Pareto type II distribution is suited in several cases of a low cell resolution. On the other hand, the K and CG-IG models characterize generally sea clutter with medium and high cell resolutions.
Citation
Ahmed BENTOUMI , Bureau de la stratégie de numérisation , Taha hocine Kerbaa , Bureau de la stratégie de numérisation , AMAR Mezache , , (2019), Model Selection of Sea Clutter Using Cross Validation Method, Procedia Computer Science, Vol:158, Issue:, pages:Pages 394-400, Elsevier
- 2018
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2018
Performance of Non-Parametric CFAR Detectors in Log-Normal and K Radar clutter
In this work, the performance of logt-, GMOS(Geometric Mean Order Statistic), TMOS(Trimmed MOS) and IE-CFAR (Inclusion/Exclusion) detectors are investigated in presence of log-normal and K distributed clutter. First, for a finite number of clutter samples, dependence of the false alarm probability P FA upon clutter parameters is examined. The CFAR property for the case of log-normal clutter is maintained while the P FA depends somewhat on the shape parameter of the K distribution. Then, by carrying out Monte-Carlo simulations, we show that for the case of log-normal clutter a small detection difference exists between the underlying CFAR detectors. In the case of K-distributed clutter, there is a significant detection difference for small values of the shape parameter (spiky clutter case).
Citation
Ahmed BENTOUMI , AMAR Mezache , Taha hocine Kerbaa , ,(2018), Performance of Non-Parametric CFAR Detectors in Log-Normal and K Radar clutter,2018 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM),Algiers, Algeria