Wilcoxon Nonparametric CFAR Scheme for Ship Detection in SAR Image

Author:

Meng Xiangwei1ORCID

Affiliation:

1. Yantai Nanshan University

Abstract

Abstract 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.

Funder

National Natural Science Foundation of China

Publisher

Research Square Platform LLC

Reference28 articles.

1. Performance of a high-resolution polarimetric SAR automatic target recognition system;Novak LM;Lincoln Lab. J.,1993

2. P. Lombardo and M. Sciotti, “Segmentation-based technique for ship detection in SAR images,” IEE Proc. Radar, Sonar Navig., vol.148, no.3, pp.147–159, Jun. 2001.

3. M. S. Liao, C. C. Wang, Y. Wang, and L. M. Jiang, “Using SAR images to detect ships from sea clutter,” IEEE Geosci. Remote Sens. Lett., vol.5, no. 2, pp.194–198, Apr. 2008.

4. G. Gao, L. Liu, L. J. Zhao, G. T. Shi, and G. Y. Kuang, “An adaptive and fast CFAR algorithm based on automatic censoring for target detection in high-resolution SAR images,” IEEE Trans. on Geosci. Remote Sens., vol.47, no.6, pp. 1685–1697, Jun. 2009.

5. B. Hou, X. Z. Chen, and L. C. Jiao, “Multilayer CFAR detection of ship targets in very high resolution SAR images,” IEEE Geosci. Remote Sens. Lett., vol.12, no.4, pp.811–815, Apr. 2015.

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