Wilcoxon Nonparametric CFAR Scheme for Ship Detection in SAR Image

IF 4.7 2区地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2025-02-13 DOI:10.1109/JSTARS.2025.3533140

Xiangwei Meng

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引用次数: 0

Abstract

The parametric constant false alarm rate (CFAR) detection algorithms, which are based on various statistical distributions, such as Gaussian, Gamma, Weibull, log-normal,

$G^{0}$

, and alpha-stable distribution, are most widely used to detect the ship targets in SAR images 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 deteriorates, whereas the advantage of the nonparametric CFAR detector that its false alarm rate is independent of the background distribution is exhibited. In this work, the Wilcoxon nonparametric CFAR scheme for the ship detection in SAR images is proposed and analyzed, and a closed form of the false alarm rate for the Wilcoxon nonparametric CFAR detector to determine the decision threshold is presented. By comparison with several typical parametric CFAR schemes on Sentinel-1A, ICEYE-X6, and Gaofen-3 SAR images, the robustness of the ability of the Wilcoxon nonparametric CFAR detector to control the actual false alarm rate at a suitably low level in different detection backgrounds is revealed, and its detection performance for the weak ships in the rough sea backgrounds is evidently improved. Moreover, the detection speed of the Wilcoxon nonparametric CFAR detector is fast, and it has a simple hardware implementation.

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来源期刊

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 地学-成像科学与照相技术

CiteScore

9.30

自引率

10.90%

发文量

563

审稿时长

4.7 months

期刊介绍： The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.