Paper
12 June 2020 An intelligent CFAR algorithm based on multi-strategy fusion
Author Affiliations +
Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 115190D (2020) https://doi.org/10.1117/12.2573249
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan
Abstract
Constant false alarm rate (CFAR) detection is an important method which is widely used in radar automatic detection. However, the performance of CFAR detection degrades dramatically in non-homogeneous environment because of the existence of interference targets and clutter in the reference window of the test cell. To the end, an intelligent multistrategy fusion (IMSF) CFAR detection algorithm is proposed in this paper. By combining the preprocessing results of FOCA-CFAR, BOCA-CFAR and OSVI-CFAR, IMSF-CFAR can utilize more suitable independent, identically distributed reference cells than conventional CFAR method, which means better detection performance. The simulation results reveal that the IMSF-CFAR maintains stable detection performance both in the homogeneous and heterogeneous environments.
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Siyuan Ouyang, Jun Tang, Wenming Yang, and Qingmin Liao "An intelligent CFAR algorithm based on multi-strategy fusion", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 115190D (12 June 2020); https://doi.org/10.1117/12.2573249
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KEYWORDS
Target detection

Environmental sensing

Sensors

Detection and tracking algorithms

Feature extraction

Facial recognition systems

Radar

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