作者: Zhibin Sun , John Davis , Wei Gao
DOI: 10.1109/TGRS.2017.2748031
关键词: Covariance and correlation 、 Kalman filter 、 Data integration 、 Remote sensing 、 Irradiance 、 Total Ozone Mapping Spectrometer 、 Sensor fusion 、 Satellite 、 Atmospheric model 、 Environmental science
摘要: Surface ultraviolet (UV) observations can be obtained from satellite or ground observations. This paper uses one data fusion technique (similar to Kalman filter) combine the advantages both sources of observations, aiming at achieving a better estimate surface UV. In this paper, new mathematical methods and algorithms were developed error covariance correlation region, which are most important components in technique. was applied Total Ozone Mapping Spectrometer (TOMS)-Ozone Monitoring Instrument (OMI) combined with measurements UV-B Research Program (UVMRP) within region continental U.S. 2005 2015. Numerical experiments showed that is effective, TOMS-OMI improved by combining UVMRP data. addition, innovative ensemble-based method generic other fields for fusion/assimilation.