近海船长分布建模与雷达舰船分类能力评估

doi:10.19665/j.issn1001-2400.2021.02.011

西安电子科技大学学报 ›› 2021, Vol. 48 ›› Issue (2): 84-91.doi: 10.19665/j.issn1001-2400.2021.02.011

近海船长分布建模与雷达舰船分类能力评估

李杉(),张坤(),水鹏朗()

西安电子科技大学雷达信号处理国家重点实验室,陕西西安 710071

收稿日期:2020-10-07 修回日期:2021-01-06 出版日期:2021-04-20 发布日期:2021-04-28
作者简介:李杉(1996—),女,西安电子科技大学硕士研究生,E-mail: li_shan@stu.xidian.edu.cn|张坤(1990—),男,西安电子科技大学博士研究生,E-mail: kzhang_1608@stu.xidian.edu.cn|水鹏朗(1967—),男,教授,博士,E-mail: plshui@xidian.edu.cn
基金资助:
国家自然科学基金(62071346)

Ship length distribution modeling on China offshore and ability evaluation of radar ship classification

LI Shan(),ZHNAG Kun(),SHUI Penglang()

National Laboratory of Radar Signal Processing,Xidian University,Xi’an 710071,China

Received:2020-10-07 Revised:2021-01-06 Online:2021-04-20 Published:2021-04-28

摘要/Abstract

摘要：

雷达高分辨距离像径向尺寸估计和航向角估计是舰船分类的主要技术手段,其分类性能与雷达分辨率、径向尺寸估计精度以及不同海域的舰船长度先验分布密切相关。通过中国船讯网采集了我国近海四大海域约30 000艘舰船的船舶自动识别系统信息,并提取了舰船长度数据。通过对舰船长度的分布拟合,发现韦布尔分布能够很好地拟合各海域的船长分布,且分布参数有明显差异。基于该先验模型,推导出了舰船的大、中、小正确分类概率与径向尺寸估计误差之间的关系。结果表明,当舰船航向角介于±75°之间时,我国近海舰船的大中小正确分类概率达到90%的条件是,舰船径向尺寸估计误差在区间(-12.67 m,9.41 m)内。

关键词: 舰船长度, 韦布尔分布, 径向尺寸估计误差, 正确分类概率

Abstract:

Radial size estimation using radar high-resolution range profiles(HRRPs) and heading angle estimation are the main means for ship classification.The classification ability is closely related to the range resolution of the radar,precision of radial size estimation,and prior distribution of ship lengths in different offshore areas.We collected the AIS information on about 30 000 ships and their lengths in the four offshore areas of China in the ship information net of China.By fitting the data of ship lengths in each offshore area,it is found that the Weibull distributions provide good-of-fitness to the ship lengths and the parameters in individual area are rather different.Based on the prior distributions of ship lengths,we derived the quantitative relationship between the correct classification probability of big-moderate-small ships and the estimate error of ship radial size.The results indicate that the condition for the big-moderate-small correct classification probability in the offshore areas of China to be up to 90% is that the estimate errors of the ship radial size estimates falls into the interval(-12.67 m,9.41 m) when the heading angle of the ship is between ±75 degrees.

Key words: ship length, Weibull distribution, estimate error of ship radial size, correct classification probability

中图分类号:

TN959.72

李杉,张坤,水鹏朗. 近海船长分布建模与雷达舰船分类能力评估[J]. 西安电子科技大学学报, 2021, 48(2): 84-91.

LI Shan,ZHNAG Kun,SHUI Penglang. Ship length distribution modeling on China offshore and ability evaluation of radar ship classification[J]. Journal of Xidian University, 2021, 48(2): 84-91.

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参考文献 17

[1]	WANG Y H, LIU H W. A Hierarchical Ship Detection Scheme for High-resolution SAR Images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012,50(10):4173-4184.
[2]	PASTINA D, SPINA C. Multi-feature Based Automatic Recognition of Ship Targets in ISAR[J]. IET Radar,Sonar and Navigation, 2009,3(4):406-423.
[3]	LANG H T, WU S W, XU Y J. Ship Classification in SAR Images Improved by AIS Knowledge Transfer[J]. IEEE Geoscience and Remote Sensing Letters, 2018,25(3):439-443.
[4]	MARGARIT G, TABASCO A. Ship Classification in Single-pol SAR Images Based on Fuzzy Logic[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011,49(8):3129-3138.
[5]	SHUI P L, ZHANG K. Ship Radial Size Estimation in High-resolution Maritime Surveillance Radars via Sparse Recovery Using Linear Programming[J]. IEEE Access, 2019,7:70673-70688.
[6]	LIAO K, GUI G, CHEN Z X, et al. High Resolution Range Profile Based Extraction of Radar Target Length[J]. International Journal of the Physical Sciences, 2011,6(23):5503-5510.
[7]	廖阔. 基于高分辨距离像的雷达自动目标识别研究[D]. 成都: 电子科技大学, 2012.
[8]	王涛, 李士国, 王秀春. 一种基于高分辨距离像的目标长度特征提取算法[J]. 中国电子科学研究院学报, 2006,1(6):532-535.
	WANG Tao, LI Shiguo, WANG Xiuchun. Extraction of Target Length Using High Resolution Range Profile[J]. Journal of China Academy of Electronics and Information Technology, 2006,1(6):532-535.
[9]	魏存伟, 段发阶, 刘先康. 基于宽带雷达HRRP舰船目标长度估计算法[J]. 系统工程与电子技术, 2018,40(9):1960-1965.
	WEI Cunwei, DUAN Fajie, LIU Xiankang. Length Estimation Method of Ship Target Based on Wide-Band Radar’s HRRP[J]. Systems Engineering and Electronics, 2018,40(9):1960-1965.
[10]	魏耀. 一种基于多约束条件的目标一维像尺寸提取方法[J]. 现代雷达, 2020,42(1):38-41.
	WEI Yao. An Extraction Method of Radar Target Length from High Resolution Range Profile with Multi-constraints[J]. Modern Radar, 2020,42(1):38-41.
[11]	李筠, 于连庆, 杨予昊. 基于高分辨距离像的空中目标长度提取方法[J]. 现代雷达, 2018,40(7):32-35.
	LI Yun, YU Lianqing, YANG Yuhao. Method of Aerial Target Length Extraction Based on High Resolution Range Profile[J]. Modern Radar, 2018,40(7):32-35.
[12]	船讯网. 船舶AIS信息[EB/OL]. [2020-03-31]. http://www.shipxy.com.
[13]	ISKANDER D R, ZOUBIR A M. Estimation of the Parameters of the K-distribution Using Higher Order and Fractional Moments[J]. IEEE Transactions on Aerospace and Electronic Systems, 1999,35(4):1435-1457.
[14]	BLACKNELL D, TOUGH R J A. Parameter Estimation for the K-distribution Based on [zlog(z)][J] IEE Proceedings:Radar,Sonar and Navigation, 2001,148(6):309-312.
[15]	胡克震. Kolmogorov-Smirnov检验法的应用[J]. 中国卫生统计, 1985(3):12-17.
	HU Kezhen. Applications of Kolmogorov-Smirnov Inspection Method[J]. Chinese Journal of Health Statistics, 1985(3):12-17.
[16]	周围. 对海ISAR目标检测估计与宽带跟踪关键技术研究[D]. 哈尔滨: 哈尔滨工业大学, 2018.
[17]	刘勇. 多源卫星舰船目标观测信息融合技术研究[D]. 长沙: 国防科技大学, 2018.

海域	小型船	中型船	大型船	总计
渤海	1 114	845	376	2 335
黄海	2 887	959	460	4 306
东海	10 997	2 503	808	14 308
南海	7 293	1 665	677	9 635
整体	2 2291	5 972	2 321	30 584

海域	瑞利分布	韦布尔分布	K-分布
整体	0.367 8	0.098 7	0.101 9
渤海	0.261 1	0.073 4	0.142 9
黄海	0.414 4	0.123 4	0.174 2
东海	0.371 2	0.115 4	0.138 1
南海	0.349 8	0.114 7	0.138 0

海域	ν	σ
整体	0.947 7	62.560 2
渤海	1.322 1	105.687 2
黄海	0.973 8	72.324 2
东海	0.925 8	55.661 5
南海	0.915 6	58.996 8

近海船长分布建模与雷达舰船分类能力评估

Ship length distribution modeling on China offshore and ability evaluation of radar ship classification

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