New Algorithm Model for Processing Generalized Dynamic Nonlinear Data Derived from Deformation Monitoring Network
被引:0
作者:
Lin Xiangguo
论文数: 0引用数: 0
h-index: 0
机构:
Shandong Agr Univ, Dept Informat Sci & Engn, Tai An 271018, Shandong, Peoples R ChinaShandong Agr Univ, Dept Informat Sci & Engn, Tai An 271018, Shandong, Peoples R China
Lin Xiangguo
[1
]
Liang Yong
论文数: 0引用数: 0
h-index: 0
机构:
Shandong Agr Univ, Dept Informat Sci & Engn, Tai An 271018, Shandong, Peoples R ChinaShandong Agr Univ, Dept Informat Sci & Engn, Tai An 271018, Shandong, Peoples R China
Liang Yong
[1
]
机构:
[1] Shandong Agr Univ, Dept Informat Sci & Engn, Tai An 271018, Shandong, Peoples R China
deformation monitoring;
generalized nonlinear data processing;
Marquardt method;
parameter estimate;
D O I:
10.1007/BF02826853
中图分类号:
TP7 [遥感技术];
学科分类号:
081102 ;
0816 ;
081602 ;
083002 ;
1404 ;
摘要:
The processing of nonlinear data was one of hot topics in surveying and mapping field in recent years. As a result, many linear methods and nonlinear methods have been developed. But the methods for processing generalized nonlinear surveying and mapping data, especially for different data types and including unknown parameters with random or nonrandom, are seldom noticed. A new algorithm model is presented in this paper for processing nonlinear dynamic multiple-period and nmltiple-accuracy data derived from deformation monitoring network.