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The multi-solution problem in 4DVar and solved in a smooth subspace
会议论文
2010 International Conference on Multimedia Technology, ICMT 2010, Ningbo, China, October 29, 2010 - October 31, 2010
作者:
Shao, Ai-Mei
;
Qiu, Xiao-Bin
;
Qiu, Chong-Jian
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  |  
浏览/下载:2/0
  |  
提交时间:2017/01/18
Mathematical models
Covariance matrix
Mathematical operators
Metadata
4DVar
Background-error covariances
Control variable
Equation models
Model data
Multi-solution problem
Numerical experiments
Observation information
Shallow-water
Shallow-water-equation model
Smooth operator
Solution problems
Transformation
Data disposal and analysis with least squares collocation in tall building health monitoring
会议论文
Wuhan, China, September 20, 2009 - September 22, 2009
作者:
Dang, Xing-Hai
;
Wei, Yu-Ming
;
Zhao, Jian-Yun
;
Yang, Yu-Li
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  |  
浏览/下载:4/0
  |  
提交时间:2020/11/15
Covariance matrix
Data handling
Function evaluation
Health
Maintenance
Subsidence
Tall buildings
Building deformations
Building operations
Covariance function
Health monitoring
High rise building
Least-squares collocation
Monitoring points
Multiple linear regressions
Spatial correlation patterns of l-band microwave brightness temperature
会议论文
2008 IEEE International Geoscience and Remote Sensing Symposium
Xujun Han
;
Xin Li
;
Rui Jin
;
Shuguo Wang
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  |  
浏览/下载:9/0
  |  
提交时间:2015/08/21
Design of GPS/INS integrated navigation system based on multisensor information fusion (EI CONFERENCE)
会议论文
6th World Congress on Intelligent Control and Automation, WCICA 2006, June 21, 2006 - June 23, 2006, Dalian, China
Chunmei H.
;
Yantao T.
;
Wanxin S.
;
Mao L.
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浏览/下载:23/0
  |  
提交时间:2013/03/25
Two kinds of design methods of GPS/INS integrated navigation system are presented
that is GPS/INS integrative system and integrated navigation system based on information fusion. By analyzing mathematics model of the first system error
we found that inertia velocity error would cause code loop track error. Consequently
the pseudo range meterage error is interrelated with inertia velocity error
which is complex to calculate. If this relativity is ignored in the state equation and observation equation of this system
it must affect the estimated precision of the kalman filter and maybe the system is unstable. Therefore
the second integrated navigation method is introduced. It adopts information fusion
federal kalman filter and covariance. And consider the above pertinence to analyze the navigation performance of the integration system. Then it gives the flow of federal kalman filter algorithm. By analyzing
the conclusion is that velocity error of integrated navigation system drops from 0.5m/s to below 0.05m/s
and improves the precision and reliability of the navigation system effectively
well continuity and real-time capability. It provides an effective way for data analysis and process of fusion navigation system. 2006 IEEE.
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