A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites

doi:10.1109/LGRS.2019.2920660

	A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites
	Li, Weifu 1,2; Zhao, Xinghui 1,2; Peng, Jiangtao 1,2; Luo, Zhicheng 1,2; Shen, Lijun2 ; Han, Hua2 ; Zhang, Peng 3; Yang, Lei 3
发表期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN	1545-598X
	2020-02-01
卷号	17 期号:2 页码:197-201
通讯作者	Yang, Lei(yangl@cma.gov.cn)
摘要	Known as input in the numerical weather prediction (NWP) models, microwave radiation imager (MWRI) data have been widely distributed to the user community. Nevertheless, the current operational geolocation accuracy is still on the pixel scale due to the presence of geolocation uncertainty. In this letter, we propose a new method to estimate the geolocation errors in MWRI data. Compared to the traditional coastline inflection method (CIM), the proposed method has two innovations. First, we establish a surface fitting interpolation model by involving more observations to detect the coastline. Second, we employ the iterative closest point (ICP) algorithm to determine the correspondences between the detected coastline and the actual coastline. Simulated experimental results demonstrate that the proposed method can provide a more accurate geolocation error estimation than the CIM. By applying our method, we have processed an MWRI data set from January 1 to February 28 in 2016. The experimental results have shown that the operational FY-3C MWRI geolocation errors are 0.4813 and 0.4909 pixels in the along-track and cross-track directions, respectively, which can be significantly reduced to 0.1299 and 0.1497 pixels after the attitude correction. It means that the geolocation accuracy has an average improvement up to 70%.
关键词	Coastline detection geolocation error measurement iterative closest point (ICP) microwave radiation imager (MWRI)
DOI	10.1109/LGRS.2019.2920660
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Problem[2018YFB0504900] ; National Key Research and Development Problem[2018YFB0504905] ; National Natural Science Foundation of China[11771130] ; National Natural Science Foundation of China[61871177] ; National Natural Science Foundation of China[61673381] ; National Natural Science Foundation of China[61701497] ; National Natural Science Foundation of China[91338109] ; National Natural Science Foundation of China[61172113] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671] ; National Key Research and Development Problem[2018YFB0504900] ; National Key Research and Development Problem[2018YFB0504905] ; National Natural Science Foundation of China[11771130] ; National Natural Science Foundation of China[61871177] ; National Natural Science Foundation of China[61673381] ; National Natural Science Foundation of China[61701497] ; National Natural Science Foundation of China[91338109] ; National Natural Science Foundation of China[61172113] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671]
项目资助者	National Key Research and Development Problem ; National Natural Science Foundation of China ; Scientific Instrument Developing Project of Chinese Academy of Sciences
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000510900300003
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	图像视频处理与分析
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/28561
专题	脑图谱与类脑智能实验室_微观重建与智能分析
通讯作者	Yang, Lei
作者单位	1.Hubei Univ, Fac Math & Stat, Wuhan 430062, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Li, Weifu,Zhao, Xinghui,Peng, Jiangtao,et al. A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2020,17(2):197-201.
APA	Li, Weifu.,Zhao, Xinghui.,Peng, Jiangtao.,Luo, Zhicheng.,Shen, Lijun.,...&Yang, Lei.(2020).A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,17(2),197-201.
MLA	Li, Weifu,et al."A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 17.2(2020):197-201.