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Geolocation Error Estimation and Correction on Long-Term MWRI Data

文献类型：期刊论文

作者Liu, Jiazheng3,4; Li, Weifu3,4; Peng, Jiangtao2; Shen, Lijun4; Han, Hua3,4; Zhang, Peng1; Yang, Lei1
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2021-11-01
卷号59期号:11页码:9448-9461
ISSN号0196-2892
关键词Geology Sea surface Satellites Earth Instruments Satellite broadcasting Microwave radiometry Geolocation error estimation and correction Micro-Wave Radiation Imager (MWRI) nonrigid point set registration
DOI10.1109/TGRS.2021.3051199
通讯作者Yang, Lei(yangl@cma.gov.cn)
英文摘要Due to the limitation of the satellite attitude measurement accuracy and the system servo control error of the payload scanning mechanism, an optimal use of Micro-Wave Radiation Imager (MWRI) observations requires high geolocation accuracy. In the operational system, the MWRI geolocation accuracy reaches 1 pixel, and there still exists room for improvement. In this article, we improve upon the coastline inflection point method (CIM) and propose to assign the accurate correspondence by employing a nonrigid point set registration method. First, the method identifies a set of latent variables to recognize outliers and then applies nonparametric geometric constraints to the correspondence as a priori distribution. Second, the maximum a posteriori (MAP) estimation is applied by the expectation-maximization (EM) algorithm to obtain correct inliers. The comparison with other methods demonstrates that the proposed method can provide more accurate estimation of geolocation bias. In addition, the pixel error and changes in spacecraft attitude with the long-term geolocation data in FY-3C MWRI before and after correction were analyzed during the period from April 1 to August 30, 2018. The results have shown that the geolocation errors are reduced from [0.50, 0.60] pixels to [0.20, 0.33] pixels in the along- and cross-track directions after the attitude correction. In addition, the reduction of the standard deviation shows that the geolocation quality of MWRI is improved.
WOS关键词MICROWAVE ; REGISTRATION ; ACCURACY ; IMAGER
资助项目National Key Research and Development Program[2018YFB0504900] ; National Key Research and Development Program[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] ; Fundamental Research Funds for the Central Universities of China[2662020LXQD002]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000711850900041
资助机构National Key Research and Development Program ; National Natural Science Foundation of China ; Scientific Instrument Developing Project of Chinese Academy of Sciences ; Fundamental Research Funds for the Central Universities of China
源URL[http://ir.ia.ac.cn/handle/173211/46500]  
专题类脑智能研究中心_微观重建与智能分析
通讯作者Yang, Lei
作者单位1.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
2.Hubei Univ, Fac Math & Stat, Hubei Key Lab Appl Math, Wuhan 430062, Peoples R China
3.Univ Chinese Acad Sci, Sch Future Technol, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Jiazheng,Li, Weifu,Peng, Jiangtao,et al. Geolocation Error Estimation and Correction on Long-Term MWRI Data[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2021,59(11):9448-9461.
APA Liu, Jiazheng.,Li, Weifu.,Peng, Jiangtao.,Shen, Lijun.,Han, Hua.,...&Yang, Lei.(2021).Geolocation Error Estimation and Correction on Long-Term MWRI Data.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,59(11),9448-9461.
MLA Liu, Jiazheng,et al."Geolocation Error Estimation and Correction on Long-Term MWRI Data".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 59.11(2021):9448-9461.

入库方式： OAI收割

来源：自动化研究所

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