Performance Evaluation of SOCA-CFAR Detectors in Weibull-Distributed Clutter Environments

Alvarado, Maria Cecilia Luna; García, Fernando Darío Almeida; Jimenez, Lenin Patricio Jimenez; Fraidenraich, Gustavo; Iano, Yuzo

doi:10.1109/lgrs.2022.3152936

IEEE Geosci. Remote Sensing Lett.

2022

DOI: 10.1109/lgrs.2022.3152936

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Performance Evaluation of SOCA-CFAR Detectors in Weibull-Distributed Clutter Environments

Maria Cecilia Luna Alvarado

Fernando Darío Almeida García

Lenin Patricio Jimenez Jimenez

et al.

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Cited by 6 publications

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An improved CFAR algorithm for multiple environmental conditions

Rihan,

Nossair,

Mubarak

2024

SIViP

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The primary objective of radar digital signal processing is to detect and identify targets in complicated situations, such as those involving clutter or several closely positioned targets. The constant false alarm rate (CFAR) method is more effective for target recognition and has better control over the false alarm rate. Many studies have been conducted on the design of CFAR, but previous CFAR algorithms have not been effective in all or most environmental fields and target scenarios. In this study, an algorithm called Censored Mean Clutter Map CFAR (CM-CM CFAR) has been developed and tested for various environmental conditions. When compared to a fixed false alarm rate, the suggested CFAR algorithm’s Monte Carlo simulation results demonstrated a high detection probability in a variety of environments. This work designs a real-time CM-CM CFAR processor using field-programmable gate array (FPGA) technologies. Xilinx ARTIX 7 FPGA technology is used to develop and map a scalable parallel framework. Consequently, the implementation required 23,741 LUTs and 1825 FF. It is verified that the complexity and operating speed of the suggested CFAR processor are extremely appropriate for real-time implementation when compared to the results of the previously proposed FPGA implementation.

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An improved CFAR algorithm for multiple environmental conditions

Rihan,

Nossair,

Mubarak

2024

SIViP

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New log-t-based CFAR detectors for a non-homogeneous Weibull Background

Detouche

Laroussi

Madjidi

2023

Physical Communication

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Performance analysis of mean level CFAR detectors in homogeneous gamma-distributed radar clutter

Kenane,

Khalfa,

Sahed

et al. 2024

International Journal of Remote Sensing

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Performance Evaluation of SOCA-CFAR Detectors in Weibull-Distributed Clutter Environments

Cited by 6 publications

References 32 publications

An improved CFAR algorithm for multiple environmental conditions

An improved CFAR algorithm for multiple environmental conditions

New log-t-based CFAR detectors for a non-homogeneous Weibull Background

Performance analysis of mean level CFAR detectors in homogeneous gamma-distributed radar clutter

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