A synthetic aperture radar sea surface distribution estimation by n-order Bezier curve and its application in ship detection

doi:10.1007/s13131-016-0924-8

CORC > 自然资源部第一海洋研究所 > 自然资源部第一海洋研究所 > 业务部门 > 海洋物理与遥感研究室

	A synthetic aperture radar sea surface distribution estimation by n-order Bezier curve and its application in ship detection
	Lang Haitao 1,2; Zhang Jie 3; Wang Yiduo 1; Zhang Xi 3; Meng Junmin 3
刊名	ACTA OCEANOLOGICA SINICA
	2016-09
卷号	35 期号:9 页码:117-125
关键词	Bezier curve nonparametric method ship detection sea surface distribution synthetic aperture radar
ISSN号	0253-505X
DOI	10.1007/s13131-016-0924-8
英文摘要	To dates, most ship detection approaches for single-pol synthetic aperture radar (SAR) imagery try to ensure a constant false-alarm rate (CFAR). A high performance ship detector relies on two key components: an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm. First, a novel nonparametric sea surface distribution estimation method is developed based on n-order Bezier curve. To estimate the sea surface distribution using n- order Bezier curve, an explicit analytical solution is derived based on a least square optimization, and the optimal selection also is presented to two essential parameters, the order n of Bezier curve and the number m of sample points. Next, to validate the ship detection performance of the estimated sea surface distribution, the estimated sea surface distribution by n-order Bezier curve is combined with a cell averaging CFAR (CA-CFAR). To eliminate the possible interfering ship targets in background window, an improved automatic censoring method is applied. Comprehensive experiments prove that in terms of sea surface estimation performance, the proposed method is as good as a traditional nonparametric Parzen window kernel method, and in most cases, outperforms two widely used parametric methods, K and G models. In terms of computation speed, a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size, which makes it can achieve a significant speed improvement to the Parzen window kernel method, and in some cases, it is even faster than two parametric methods. In terms of ship detection performance, the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors, resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.
资助项目	Beijing Higher Education Young Elite Teacher Project[YETP0514]
WOS研究方向	Oceanography
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000383924200015
内容类型	期刊论文
源URL	[http://ir.fio.com.cn/handle/2SI8HI0U/3368]
专题	业务部门_海洋物理与遥感研究室
作者单位	1.Beijing Univ Chem Technol, Sch Sci, Beijing 100029, Peoples R China; 2.Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Big Data Anal Technol B DAT, Nanjing 210044, Jiangsu, Peoples R China; 3.State Ocean Adm, Inst Oceanog 1, Qingdao 266061, Peoples R China
推荐引用方式 GB/T 7714	Lang Haitao,Zhang Jie,Wang Yiduo,et al. A synthetic aperture radar sea surface distribution estimation by n-order Bezier curve and its application in ship detection[J]. ACTA OCEANOLOGICA SINICA,2016,35(9):117-125.
APA	Lang Haitao,Zhang Jie,Wang Yiduo,Zhang Xi,&Meng Junmin.(2016).A synthetic aperture radar sea surface distribution estimation by n-order Bezier curve and its application in ship detection.ACTA OCEANOLOGICA SINICA,35(9),117-125.
MLA	Lang Haitao,et al."A synthetic aperture radar sea surface distribution estimation by n-order Bezier curve and its application in ship detection".ACTA OCEANOLOGICA SINICA 35.9(2016):117-125.