Application of Bounded Ellipsoid Uncertainty Adjustment Algorithm to Ill-Conditioned Problem
Abstract In this paper, ellipsoidal constraints are used to describe the bounded prior information of observation vectors and parameters, which are incorporated into the measurement adjustment model. A new adjustment criterion is established to suppress discomfort. Simulation examples and ill-conditioned data of the distance-measuring network are given to show the advantages and disadvantages of ellipsoidal constraint algorithm and other methods,and verify the validity of the bounded ellipsoidal uncertainty adjustment method in dealing with ill-posed problems.
Key words :
uncertainty
ellipsoid constraint
ill-conditioned problem
ridge estimation
Cite this article:
XIA Yuguo,SONG Yingchun. Application of Bounded Ellipsoid Uncertainty Adjustment Algorithm to Ill-Conditioned Problem[J]. jgg, 2019, 39(9): 956-959.
XIA Yuguo,SONG Yingchun. Application of Bounded Ellipsoid Uncertainty Adjustment Algorithm to Ill-Conditioned Problem[J]. jgg, 2019, 39(9): 956-959.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2019/V39/I9/956
[1]
ZHAI Xinyi,PAN Guangyong,CHEN Yang,LIU Guolin. L-Curve Characteristic Value Correction Iteration Method for SBAS-InSAR Deformation Inversion [J]. jgg, 2021, 41(4): 403-407.
[2]
YANG Qiuwei,BAI Zhichao,LI Cuihong. Biased Estimation Method Based on Neumann Series [J]. jgg, 2020, 40(5): 512-516.
[3]
XIA Yuguo,SONG Yingchun,ZHAO Shaojie. An Iterative Algorithm for Adjustment Model with Uncertainty and Inequality Constraints [J]. jgg, 2020, 40(2): 152-155.
[4]
ZUO Tingying, CHEN Bangju, SONG Yingchun. Adjustment Algorithm with Spherical Constraint and Application [J]. jgg, 2020, 40(1): 71-76.
[5]
LIU Jie,ZHANG Juanjuan. A Processing Method of Ill-Posed Problems Based on Conjugate Gradient Search [J]. jgg, 2019, 39(8): 863-868.
[6]
WU Guangming, LU Tieding. Ridge Estimation Iterative Method for Illness Data Processing [J]. jgg, 2019, 39(2): 178-183.
[7]
XIA Yuguo,SONG Yingchun,XIE Xuemei. Subspace Truncation Newton Method for Parameter-Bounded Adjustment Problem [J]. jgg, 2019, 39(2): 184-188.
[8]
JI Kunpu. A Regularized Solution and Accuracy Evaluation of Ill-PosedTotal Least Squares Problem with Equality Constraints [J]. jgg, 2019, 39(12): 1304-1309.
[9]
JIANG Pan;YOU Wei. The Improved Iteration Method by Correcting Characteristic Value for Transformation of Three-Dimensional Coordinates Based on Large Rotation Angle and Quaternions [J]. jgg, 2019, 39(11): 1182-1187.
[10]
TAO Wuyong,HUA Xianghong,LU Tieding,CHEN Xijiang,ZHANG Wei. A Total Least Squares Algorithm for Non-Equidistant GM(1,1) Model and Its Ill-Posed Problem [J]. jgg, 2019, 39(1): 45-50.
[11]
WU Guangming,LU Tieding,DENG Xiaoyuan,QIU Dechao. A New Method of Constructing Regularized Matrix [J]. jgg, 2019, 39(1): 61-65.
[12]
XIAO Zhaobing,SONG Yingchun,XIE Xuemei. Application of Parameters with Ellipsoidal Constraints in Adjustment Algorithm [J]. jgg, 2018, 38(9): 964-967.
[13]
XIAO Zhaobing,SONG Yingchun,XIE Xuemei. Application of a Method for Obtaining Uncertainty in Dislocation Model [J]. jgg, 2018, 38(8): 857-861.
[14]
LU Tieding, ZHU Guohong. Algorithms for Adjustment Model with Uncertainty Based on F-Norm [J]. jgg, 2018, 38(6): 557-561.
[15]
ZHAO Zhe,ZUO Tingying,SONG Yingchun. A Method for Solving Ill-Posed Problems with Fuzzy Prior Information [J]. jgg, 2018, 38(5): 524-528.