改进的SAR图像双参数CFAR舰船检测算法

艾加秋; 齐向阳; 禹卫东

doi:10.3724/SP.J.1146.2008.01707

改进的SAR图像双参数CFAR舰船检测算法

doi: 10.3724/SP.J.1146.2008.01707

艾加秋^{①②;齐向阳},
齐向阳,
禹卫东

计量
- 文章访问数: 3475
- HTML全文浏览量: 143
- PDF下载量: 1427
- 被引次数: 0
出版历程
- 收稿日期: 2008-12-15
- 修回日期: 2009-06-18
- 刊出日期: 2009-12-19

Improved Two Parameter CFAR Ship Detection Algorithm in SAR Images

Ai Jia-qiu^{①②;齐向阳},
Qi Xiang-yang,
Yu Wei-dong

摘要

摘要: 双参数CFAR检测中设置了目标窗口、保护窗口和背景窗口3个窗口，并且窗口的大小，滑动步长都要进行经验训练得到，效率低，对距离很近的舰船SAR图像会产生漏检。针对这些不足, 该文提出了一种改进的双参数CFAR检测算法，该算法只取目标窗口和背景窗口，通过把泄露到背景窗口中的舰船部分去除并对背景窗口中的剩余部分进行均值和方差估计来检测舰船，并且将窗口滑动步长取为目标窗口尺寸。相对双参数CFAR算法，结构得到了简化，检测结果的虚警率减小, 对距离很近的舰船不会产生漏检, 计算效率得到了改善。仿真结果表明了方法的有效性。
- 舰船检测; 双参数; 恒虚警; 背景杂波提取
Abstract: In all the algorithms of the ship detection of SAR images, two parameter CFAR detector uses three moving windows: target window, protect window and background window, the sizes of the three windows and the moving step need to be trained, So it is quite inefficient and will cause targets undetected when they are too close. The improved two parameter CFAR detector delivered in this paper only uses a target window and a background window, By using special methods to remove the leaked ship pixels in the background window and estimate the remaining pixels in the background window which are sea clutter to get the local windows clutter gray mean and variance. The moving step is the same as the length of the target window, Compared with two parameter CFAR detector, the structure is simplified and the detection results false alarms is less, targets too close can also be detected, furthermore, the computing efficiency is improved. The simulation results prove the algorithms effectiveness.

HTML全文

参考文献(1)

种劲松, 朱敏慧. SAR 图像舰船目标检测算法的对比研究[J].信号处理, 2003, 19(6): 580-582.Chong Jin-song and Zhu Min-hui. Comparison on ship targetdetection algorithms of SAR imagery [J]. Signal Processing,2003, 19(6): 580-582.[2]种劲松, 朱敏慧. SAR 图像窗口K-分布目标检测算法[J].电子与信息学报.2003, 25(9):1276-1280浏览[3]谢明鸿, 张亚飞, 付琨. 基于种子点增长的SAR 图像海岸线自动提取算法[J]. 中国科学院研究生院学报, 2007, 24(1):93-98.Xie Ming-hong, Zhang Ya-fei, and Fu Kun. Algorithm ofdetection coastline from SAR images based on seedsgrowing[J]. Journal of the Graduate School of the ChineseAcademy of Sciences Technology, 2007, 24(1): 93-98.[4]陈德元, 凃国防. 一种基于小波变换的SAR 图像舰船检测的新算法[J].电子与信息学报.2007, 29(4):855-858浏览[5]郝程鹏, 侯朝焕. 一种K-分布杂波背景下的双参数恒虚警检测器[J].电子与信息学报.2007, 29(3):756-759浏览[6]Eldhuset K. An automatic ship and ship wake detectionsystem for spaceborne SAR images in coastal regions [J].IEEE Transactions on Geoscience and Remote Sensing.1996,34(4):1010-1019[7]Blake A P, Blacknell D, and Oliver C J. Sea clutter analysisand its resolution dependence[C]. Radar conference 97,Edinburgh, UK, Oct.14-16, 1997: 124-128.[8]Li Hai-yan and He Yi-jun. Detection of weak ship signals withthe optimization of polarimetric contrast enhancement [J].High Technology Letters, 2008, 14(1): 85-91.[9]Robertson N.nullet al.. Ship surveillance using RADARSATScanSAR images[J].. Ship Detection in Coastal WatersWorkshop 2000, NS, Canada, 31 May, 12 June.2000,:-[10]Crisp D J. The State-of-art in ship detection in syntheticaperture radar image[R]. Defence Science and TechnologyOrganization (DSTO)Information Science Laboratory,Edinburgh, Australia, 2004: 16-54.[11]何友等. 雷达自动检测与恒虚警处理[M]. 北京: 清华大学出版社, 1999: 81-90.He You, et al.. Radar Automatic Detection and CFARProcessing [M]. Beijing: Tsinghua University Press, 1999:81-90.

施引文献

资源附件(0)

访问统计