Journal
IET RADAR SONAR AND NAVIGATION
Volume 13, Issue 1, Pages 104-112Publisher
WILEY
DOI: 10.1049/iet-rsn.2018.5160
Keywords
signal detection; Monte Carlo methods; target tracking; object detection; radar signal processing; radar clutter; radar detection; Grubbs criterion; nonhomogeneous background; constant false alarm rate; desired property; automatic target detection; modified cell averaging CFAR detector; CA-CFAR; CFAR property; exponential-distributed background; detection performances; multiple targets; clutter edges; different significance levels; similar detection performance; homogenous environment; CAG-CFAR detector attains; similar alarm rate control; acceptable false alarm rate control; multiple-target scenario; robust detection performance; multiple-target situation; interfering targets
Funding
- Special Research Foundation for Harbin Science and Technology Innovation Talents [RC2014XK009022]
- National Natural Science Foundation of China key project [61132005]
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Constant false alarm rate (CFAR) is the desired property for automatic target detection in an unknown and non-stationary background. Here, a modified cell averaging CFAR (CA-CFAR) detector based on the Grubbs criterion (CAG-CFAR) is proposed for target detection in non-homogeneous background. The CFAR property of the CAG-CFAR with respect to the distribution parameter in exponential-distributed background is verified via Monte Carlo simulations. The detection performances of the proposed method in scenarios of multiple targets and clutter edges are investigated with different significance levels of the Grubbs criterion and sizes of reference window. Results show that the CAG-CFAR detector exhibits a similar detection performance as the CA-CFAR in homogenous environment with an appropriate significance level. At clutter edges, the CAG-CFAR detector attains a similar and acceptable false alarm rate control compared to several relevant competitors. In the multiple-target scenario, the proposed method achieves a robust detection performance with a low computational burden, whereas the competitors suffer performance degradations in varying degree. Simulations and experimental results verify the effectiveness and superiority of the proposed method in multiple-target situation with an unknown number of the interfering targets.
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