Trimodal Generalized Gamma Distribution of Sea Echoes and CFAR Detection in CG-LNT Clutter with Multiple Order Statistics
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Date
2025-06-30
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UNIVERSITY OF M'SILA
Abstract
In this thesis, a comprehensive study of radar systems and their basic concepts are presented firstly. Next, the problem of interference faced by radars and its impact on detection accuracy is also evoked. Then, radar clutter types and targets fluctuating models are also highlighted. Research works concerned in this thesis deal with the improvements of high resolution sea clutter modeling and CFAR detection in presence of interfering targets.
The first research problem focuses on the use of mixture generalized gamma (GG) distribution named Trimodal GG distribution in order to provide an accurate model that reflects the description characteristics of the majority of sea clutter scenarios. Comparison purposes are conducted against GG, mixture of two GG, K+noise and CG-LNT+noise (Compound Gaussian Log-Normal Texture) models. Parameters estimation is obtained by the well known LSA (Least Squares Approximation) approach. The modeling results show that the proposed Trimodal GG model is able to fit most scenes of IPIX (Intelligent PIxel X-band radar) real data.
The second research problem is to enhance CFAR (Constant False Alarm Rate) properties in presence of homogeneous and heterogeneous CG-LNT sea clutter. To achieve this, existing WHWH (Weber Haykin-Weber Haykin))-CFAR and OS (Order Statistic)-CFAR algorithms are combined by means of a general test statistic. This detector is labeled WHWHOS-CFAR and is compared with available logt-, OS-, WH-, WHOS- and WHWH-CFAR detectors. Through, simulated and IPIX real data, it is shown that the proposed WHWHOS-CFAR detector exhibits the best CFAR properties and provides a worst CFAR loss only for a special value of the standard deviation clutter parameter.
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Keywords
Sea clutter, Trimodal GG model, CFAR detection, CG-LNT distribution, WHWHOS-CFAR detector.