Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Science of Surveying and Mapping》 2019-01
Add to Favorite Get Latest Update

Constrained adaptive robust weighted total least-squares filtering

BAI Zhengdong;LI Shuai;CHEN Bobo;LI Qi;Institute of Geomatics,Department of Civil Engineering,Tsinghua University;  
Aiming at various complicated problems in the implementation of the new high-speed railway track deformation monitoring,this paper proposed and deducted an adaptive robust weighted total least-squares filtering algorithm with constraints,each element of the rotation matrix was designed as state parameters,with the unit orthogonality of the matrix as a constraint condition of the parameters,the accuracy of the position resolution was improved by about 29% compared with the Kalman filtering.Experiments showed that this algorithm was more suitable for the application scenario of high-speed railway track deformation monitoring than the traditional method.At the same time,this algorithm can be applied to any situation that needs to take into account the gross error in the observation equation and the random error in the coefficient matrix,the deviation of the dynamic model,and the state parameters with arbitrary constraints,including other measurement,positioning,and navigation scenarios.
【Fund】: 国家重点研发计划项目(2017YFB0504202);; 山东省重点研究计划项目(2016ZDJS03A08)
【CateGory Index】: U216.3
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved