Wilcoxon Nonparametric CFAR Scheme for Ship Detection in SAR Image
Xiangwei Meng
The parametric constant false alarm rate (CFAR) detection algorithms which
are based on various statistical distributions, such as Gaussian, Gamma,
Weibull, log-normal, G0 distribution, alpha-stable distribution, etc, are most
widely used to detect the ship targets in SAR image at present. However, the
clutter background in SAR images is complicated and variable. When the actual
clutter background deviates from the assumed statistical distribution, the
performance of the parametric CFAR detector will deteriorate. In addition to
the parametric CFAR schemes, there is another class of nonparametric CFAR
detectors which can maintain a constant false alarm rate for the target
detection without the assumption of a known clutter distribution. In this work,
the Wilcoxon nonparametric CFAR scheme for ship detection in SAR image is
proposed and analyzed, and a closed form of the false alarm rate for the
Wilcoxon nonparametric detector to determine the decision threshold is
presented. By comparison with several typical parametric CFAR schemes on
Radarsat-2, ICEYE-X6 and Gaofen-3 SAR images, the robustness of the Wilcoxon
nonparametric detector to maintain a good false alarm performance in different
detection backgrounds is revealed, and its detection performance for the weak
ship in rough sea surface is improved to some extent. Moreover, the Wilcoxon
nonparametric detector can suppress the false alarms resulting from the
sidelobes at some degree and its detection speed is fast.