A method of generalized inverse adjustment based on improved Gram-Schmidt orthogonalization
被引:0
作者:
Luo, Sanming
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机构:
First Crust Deformation Monitoring and Application Center, CEA, 7 Naihuo Road, Tianjin 300180, ChinaFirst Crust Deformation Monitoring and Application Center, CEA, 7 Naihuo Road, Tianjin 300180, China
Luo, Sanming
[1
]
Bo, Wanju
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h-index: 0
机构:
First Crust Deformation Monitoring and Application Center, CEA, 7 Naihuo Road, Tianjin 300180, ChinaFirst Crust Deformation Monitoring and Application Center, CEA, 7 Naihuo Road, Tianjin 300180, China
Bo, Wanju
[1
]
Huang, Quhong
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机构:
First Geodetic Surveying Brigade, SBSM, 4 Cehui Road, Xi'an 710054, ChinaFirst Crust Deformation Monitoring and Application Center, CEA, 7 Naihuo Road, Tianjin 300180, China
Huang, Quhong
[2
]
Wang, Xining
论文数: 0引用数: 0
h-index: 0
机构:
First Geodetic Surveying Brigade, SBSM, 4 Cehui Road, Xi'an 710054, ChinaFirst Crust Deformation Monitoring and Application Center, CEA, 7 Naihuo Road, Tianjin 300180, China
Wang, Xining
[2
]
机构:
[1] First Crust Deformation Monitoring and Application Center, CEA, 7 Naihuo Road, Tianjin 300180, China
[2] First Geodetic Surveying Brigade, SBSM, 4 Cehui Road, Xi'an 710054, China
来源:
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University
|
2012年
/
37卷
/
02期
关键词:
Covariance matrix - Defects - Inverse problems;
D O I:
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中图分类号:
学科分类号:
摘要:
Starting directly with coefficient matrix of condition equation or error equation, the least square solution by triangulation decomposition on coefficient matrix is carried on with improved Gram-Schmidt orthogonalization procedure. Then, the math formula and the calculation steps of solving generalized inverse matrix on improved Gram-Schmidt algorithm are deduced. The unknown solution vectors and the mathematical expression of the variance-covariance matrix are given through the generalized inverse expression. Two examples are used to verify its effect, and the results show that the modified Gram-Schmidt orthogonal method can process any matrix including rank defect array.