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2021-10-20

Enhancing Detection Performances of Nonhomogeneous Weibull Clutter by Knowledge Based Systems Exploitation

By Abdellatif Rouabah, M'hamed Hamadouche, Djamal Teguig, and Hamza Zeraoula
Progress In Electromagnetics Research B, Vol. 94, 53-74, 2021
doi:10.2528/PIERB21082004

Abstract

This article aims to study the behavior of Constant False Alarm Rate (CFAR) detectors for a heterogeneous Weibull clutter and its derivatives. CFAR architectures based on exploitation of the Combined Environmental Knowledge Base (CEKB) have been proposed, called Knowledge Based Systems-Maximum Likelihood-CFAR (KBS-ML-CFAR) and KBS-Log-t-CFAR for nonhomogeneous Weibull clutter at general parameters. A CFAR architecture that uses Geographic Information System (GIS) as a Knowledge Base (KB), called KBS-Forward Automatic Order Selection Ordered Statistics-CFAR (KBS-FAOSOS-CFAR) has been proposed for special Weibull parameters. The performances of the proposed detectors have been studied and analyzed by conducting MATLAB simulations. The simulation results show that the KBS-CFAR based on CEKB outperforms the ML and Log-t-CFAR in terms of clutter edge detection capability in nonhomogeneous Weibull clutter case. Compared with other KB, this KBS-CFAR based on CEKB performs well to preserve the probability of false alarm (Pfa) at a desired constant value. For special Weibull parameters, the proposed KBS-FAOSOS-CFAR based on GIS performs better than KBS-Dynamic-CFAR and KBS-Adaptive Linear Combined-CFAR (KBS-ALC-CFAR) in severe interference case. CFAR techniques have been implemented on the ADSP (Advanced Digital Signal Processor) processing board, and the results have been evaluated and discussed.

Citation


Abdellatif Rouabah, M'hamed Hamadouche, Djamal Teguig, and Hamza Zeraoula, "Enhancing Detection Performances of Nonhomogeneous Weibull Clutter by Knowledge Based Systems Exploitation," Progress In Electromagnetics Research B, Vol. 94, 53-74, 2021.
doi:10.2528/PIERB21082004
http://jpier.org/PIERB/pier.php?paper=21082004

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