DEFORMATION MONITORING NETWORK ADJUSTMENT WITH
CONSIDERING PRIOR INFORMATION
1）Department of Surveying Engineering, Changsha University of Science & Technology, Changsha 410004
Abstract The deformation monitoring network adjustment method with considering the prior information are the paper researched. The functional model is given and the optimum solution formulas are deduced. Whether the prior information is considered or not, the parameter estimation formulas are the same. The estimation accuracy and applicable condition analysis were also carried out. The study reveals the relationships among prior accuracy, the quality of virtual observations and the adjustment accuracy. The calculation example of deformation monitoring network adjustment shows that considering the prior information can improve the accuracy of the parameter estimation
Key words ：
parameter estimation
prior information
deformation monitoring
Bayes estimation
surveying adjustment
Received: 09 November 2012
Published: 18 April 2013
Cite this article:
Deng Xingsheng,Cheng Shiqiao,Ding Meiqing. DEFORMATION MONITORING NETWORK ADJUSTMENT WITH
CONSIDERING PRIOR INFORMATION[J]. jgg, 2013, 33(2): 45-48.
Deng Xingsheng,Cheng Shiqiao,Ding Meiqing. DEFORMATION MONITORING NETWORK ADJUSTMENT WITH
CONSIDERING PRIOR INFORMATION[J]. jgg, 2013, 33(2): 45-48.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2013/V33/I2/45
[1]
TANG Jun，LI Yinjian，GAO Xin. GNSS Deformation Monitoring Denoising Method Based on CEEMDAN
[2]
YUAN Zhiming, LI Peihong, LIU Xiaosheng. Study on the Application of Improved PSO-SVM Model Considering Neighbor-Point in the Settlement Prediction of Foundation Pit
[3]
XIE Bo, LIU Lianwang. Calculation of Rank-Defective Indirect Adjustment Model with Constraint by Inverting Block Matrix
[4]
LU Tieding，XIE Jianxiong. Deformation Monitoring Data De-Noising Method Based on Variational Mode Decomposition Combined with Sample Entropy
[5]
YUE Cong,WANG Li,WANG Zhiwei,HAN Qingqing,XU Fu. Information Extraction and Noise Suppression of GNSS Landslide Deformation Based on S-Transformation
[6]
YUAN Debao,ZHANG Zhenchao,ZHANG Jun,ZAHNG Jian. Application of Optimized Fractional Order EGM (1,1) Model in Deformation Monitoring and Forecasting
[7]
WANG Zhiwei,WANG Li,HAN Qingqing,XU Fu,YUE Cong. Data Decoding Method of the Displacement Sensor and ItsApplication in Landslide Monitoring
[8]
ZUO Tingying, CHEN Bangju, SONG Yingchun. Adjustment Algorithm with Spherical Constraint and Application
[9]
GAN Ruo,CHEN Tianwei,ZHENG Xudong,DUAN Qingda,PAN Mei. Research on Denoising of Deformation Monitoring Data by Improved Wavelet Threshold Function
[10]
WEN Yaxin,DAI Wujiao. A Single Epoch Ambiguity Algorithm for Medium and Long Baseline in Deformation Monitoring
[11]
WANG Leyang,DING Rui,WU Lulu. Partial EIV Model Variance Component Estimation and Accuracy Evaluation of SUT Method by Deviation Correction
[12]
LU Lu,FAN Hongdong,ZHENG Meinan,ZOU Hao. Dynamic Settlement Monitoring and Time Series Analysis of Railway in Mining Area Based on TCP-InSAR
[13]
LUO Gan,LIANG Yueji,HUANG Yibang. Deformation Analysis Based on a Dual-Tree Complex Wavelet Transform Method
[14]
XIAO Zhaobing,SONG Yingchun,XIE Xuemei. Application of Parameters with Ellipsoidal Constraints in Adjustment Algorithm
[15]
DENG Xingsheng,HUANG Xiaopeng,PENG Sichun. Weighted Total Least-Squares Adjustment with Partial Prior Random Parameter
