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Optimization of Distributed OS-CFAR and CMLD-CFAR Detectors using Differential Evolution Algorithm

  • Research Article-Electrical Engineering
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Abstract

In this paper, we analyze the performance of the Differential Evolution (DE) compared with the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) applied to the optimization of the detection thresholds of distributed Ordered Statistics Constant False Alarm Rate (OS-CFAR) and Censored Mean Level Detector (CMLD-CFAR) systems using “OR” and “AND” fusion rules at the fusion center. The global systems’ detection performance is analyzed in a Gaussian clutter considering identical and non-identical CFAR detectors. The obtained results showed that the DE optimization technique gives better performance than PSO and GA in both cases, either in identical or non-identical CFAR detectors.

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Authors and Affiliations

  1. Laboratoire Signaux Et Systemes de Communication, Departement d’electronique Universite Constantine 1, Constantine, 25000, Algeria

    M. A. Bouteldja, M. Baadeche & F. Soltani

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  1. M. A. Bouteldja
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  2. M. Baadeche
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  3. F. Soltani
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Correspondence to F. Soltani.

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Bouteldja, M.A., Baadeche, M. & Soltani, F. Optimization of Distributed OS-CFAR and CMLD-CFAR Detectors using Differential Evolution Algorithm. Arab J Sci Eng 47, 3355–3365 (2022). https://doi.org/10.1007/s13369-021-06203-4

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  • DOI: https://doi.org/10.1007/s13369-021-06203-4

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