一种改进的恒虚警海事雷达图像目标检测方法  

An Improved CFAR Target Detection Method for Maritime Radar Image

作　　者：曹桂林 冯辉[1,2] 徐海祥[1,2] 李文娟 CAO Guilin;FENG Hui;XU Haixiang;LI Wenjuan(Key Laboratory of High Performance Ship Technology,Ministry of Education,Wuhan University of Technology,Wuhan 430063,China;School of Naval Architecture,Ocean and Energy Power Engineering,Wuhan University of Technology,Wuhan 430063,China;Marine Equipment and Technology Institute,Jiangsu University of Science and Technology,Zhenjiang 212000,China)

机构地区：[1]武汉理工大学高性能船舶技术教育部重点实验室,武汉430063 [2]武汉理工大学船海与能源动力工程学院,武汉430063 [3]江苏科技大学海洋装备研究院,镇江212000

出　　处：《武汉理工大学学报（交通科学与工程版）》2023年第1期115-120,共6页Journal of Wuhan University of Technology（Transportation Science & Engineering）

基　　金：国家自然科学基金(51879210,51979210);中央高校基本科研业务费专项资金(2019Ⅲ040,2019III132CG)。

摘　　要：文中提出了一种改进的恒虚警检测器(Improved MVI-CFAR,IMVI-CFAR).该检测器结合均值类(ML)和有序统计类(OS)等CFAR检测器的优势,在可变性指数的作用下,自适应采用不同场景下合适的CFAR算法,通过仿真实验验证了IMVI-CFAR检测器的优势.结果表明:相较于传统CFAR检测器和其他自适应CFAR检测器,IMVI-CFAR在多目标干扰、杂波边缘环境中和海事雷达图像多目标场景中均有更好的检测性能.An improved constant false alarm rate detector(IMVI-CFAR) was proposed. This detector combined the advantages of CFAR detectors such as mean class(ML) and ordered statistics class(OS), and adaptively adopts appropriate CFAR algorithms in different scenarios under the effect of variability index. The advantages of IMVI-CFAR detector were verified by simulation experiments. The results show that compared with the traditional CFAR detector and other adaptive CFAR detectors, IMVI-CFAR has better detection performance in multi-target interference, clutter edge environment and multi-target scenes in maritime radar images.

关 键 词：智能船舶 海事雷达图像 多目标干扰 恒虚警 

分 类 号：U675[交通运输工程—船舶及航道工程]