A New Adaptive CFAR Detector

Congan Xu; Tao Jian; You He; Xin Feng Gu

doi:10.4028/www.scientific.net/AMM.127.598

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 127A New Adaptive CFAR Detector

A New Adaptive CFAR Detector

Abstract:

A new CFAR detector based on Grubbs statistic called G-CFAR detector is proposed and its detection architecture is given.in this paper. Also the values of the threshold in different confidence level are given. The G-CFAR is evaluated through Monte-Carlo simulation in various environments. In homogeneous background, the performance of G-CFAR shows a little worse than that of CA-CFAR. In multiple targets background, the G-CFAR performs robustly, especially when the interfering targets are not confined to a single half of the reference window, the G-CFAR keeps good performance, while the VI-CFAR can not detect the targets effectively .

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Periodical:

Applied Mechanics and Materials (Volume 127)

Pages:

598-602

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.127.598

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Online since:

October 2011

Authors:

Congan Xu, Tao Jian, You He, Xin Feng Gu

Keywords:

Constant False Alarm Rate (CFAR), Grubbs Statistic, Multiple Targets Background, Radar Target Detection

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References

[1] He You, Guan Jian, Peng Yingning, etc. Automatic radar detection and constant false alarm rate processing [M]. Beijing: Tsinghua University Press, 1999, 33. (In Chinese).

Google Scholar

[2] Finn H M, Johnson R S. Adaptive detection mode with threshold control as a function of spatially sampled clutter-level estimates [J]. RCA Review, 1968, 29(9): 414-464.

Google Scholar

[3] Hansen V G. Constant False Alarm Rate Processing in Search Radars [C]/Proceeding IEE International Radar Conference, London, (1973).

Google Scholar

[4] Trunk G V. Range Resolution of Targets Using Automatic Detectors [J]. IEEE Trans on Aerospace and Electronic System, 1978, 14(5): 750-755.

DOI: 10.1109/taes.1978.308625

Google Scholar

[5] Smith M E, Varshney P K. Intelligent CFAR processor based on data variability [J]. IEEE Trans. on Aerospace and Electronic System, 2000, 36(3): 837-847.

DOI: 10.1109/7.869503

Google Scholar

[6] Liu Ying, Wei Gong. The Improvement M ethod of Grubbs Test in Clinical Laboratory'S Internal Quality Control [J]. Henan Science, 2006, 24(5): 641-644.

Google Scholar