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

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 r...

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Bibliographic Details
Published in:Signal, image and video processing image and video processing, 2023-06, Vol.17 (4), p.1105-1111
Main Authors: Zebiri, Khaled, Mezache, Amar
Format: Article
Language:English
Subjects:
Clutter
Computer Imaging
Computer Science
Constant false alarm rate
Image Processing and Computer Vision
Mean
Multimedia Information Systems
Original Paper
Pattern Recognition and Graphics
Radar detection
Radar targets
Signal,Image and Speech Processing
Statistical analysis
Target detection
Vision
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Summary: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.
ISSN:1863-1703
1863-1711
DOI:10.1007/s11760-022-02317-w