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航空遥感数据同化算法集成计算与可视化
引用本文:王皓玉,秦思娴,马建文,尤红建.航空遥感数据同化算法集成计算与可视化[J].计算机工程与应用,2012,48(7):124-127,153.
作者姓名:王皓玉  秦思娴  马建文  尤红建
作者单位:1. 中国科学院 对地观测与数字地球科学中心,北京100094;中国科学院研究生院,北京100049
2. 中国科学院研究生院,北京,100049
3. 中国科学院电子学研究所,北京,100190
基金项目:“国家航空遥感系统”的子课题项目
摘    要:遥感数据同化技术在动力模型框架内,使用数据同化算法对动力模型输出的定量(物理、化学量)数据与观测数据进行一致性处理与结果误差分析。将多源遥感数据同化到动力模型预测与参数估计中,可帮助改善地表、大气和海洋变化的分析和预测精度。以国家发改委"十二五"建设的国家航空遥感系统项目为依托,针对航空遥感系统10种传感器设计开发数据同化系统。因无法找到适用于该系统的3DVAR和EnKF算法程序,必须自主开发核心算法程序。介绍了研究开发的航空遥感数据同化算法集成计算与可视化系统及其核心算法的关键技术流程。实验结果证实,该系统可以有效地对航空遥感数据进行同化。

关 键 词:航空遥感传感器  数据同化  集成计算  可视化  同化系统

Assimilation algorithm integrated computing and visualization for airborne remote sensing data
WANG Haoyu , QIN Sixian , MA Jianwen , YOU Hongjian.Assimilation algorithm integrated computing and visualization for airborne remote sensing data[J].Computer Engineering and Applications,2012,48(7):124-127,153.
Authors:WANG Haoyu  QIN Sixian  MA Jianwen  YOU Hongjian
Affiliation:1.Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China 2.Graduate University of the Chinese Academy of Sciences, Beijing 100049, China 3.Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
Abstract:Remote sensing data assimilation techniques process quantitative parameters(physical, chemical parameters from dynamic model)and observation parameters with data assimilation algorithms in the framework of the dynamic model, get parameters analysis results. Assimilating multi-source remote sensing data into dynamic model estimating and forecasting can help to improve the prediction of analysis and accuracy. This paper developes an airborne remote sensing data assimilation system for China airborne remote sensing system. Since no obtainable algorithms(3DVAR and EnKF)procedures fit to this system, self-development of the core algorithms program is necessary. This paper describes the key technical processes of the development of airborne remote sensing data assimilation algorithms integrated computing and visualization system and its core algorithms. Experimental results show that the system is effective for airborne remote sensing data assimilation.
Keywords:airborne remote sensing sensors  data assimilation  integrated computing  visualization  data assimilation system
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