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Triple-order statistics-based CFAR detection for heterogeneous Pareto type I background

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Abstract

For non-stationary radar returns, constant false alarm rate (CFAR) schemes are derived to maintain the probability of false alarm in its desired value. Non-coherent CFAR processes based upon scale and power-invariant distributions for sea clutter received a lot of attention and it is still an open research area in radar target detection. In this context, a novel CFAR detector-labeled WHOS-CFAR (Weber–Haykin-Order Statistics) is proposed in this paper for a Pareto type I sea clutter. The decision rule is given in terms of three ranked samples allowing full CFAR properties with respect to clutter shape and scale parameters. Through Monte-Carlo simulations, the detection performances are illustrated with and without interfering targets. It is shown that the WHOS-CFAR keeps almost the CFAR property compared to existing logt- WH-, GMOS- (Geometric Mean-Order Statistic), TMOS-(Trimmed Mean-Order Statistic) and IE (Inclusion/Exclusion)-CFAR detectors.

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Authors and Affiliations

  1. Laboratoire Signaux Et Systems de Communication, Département d’électronique, Université Des Frères Mentouri Constantine, Constantine, Algeria

    Khaled Zebiri

  2. Laboratoire Signaux Et Systéms de Communication, Département d’éléctronique, Universitré Mohamed Boudiaf M’sila, 28000, M’sila, Algeria

    Amar Mezache

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  1. Khaled Zebiri
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  2. Amar Mezache
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Correspondence to Khaled Zebiri.

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Zebiri, K., Mezache, A. Triple-order statistics-based CFAR detection for heterogeneous Pareto type I background. SIViP 17, 1105–1111 (2023). https://doi.org/10.1007/s11760-022-02317-w

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  • DOI: https://doi.org/10.1007/s11760-022-02317-w

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