Application of Sigma Point Kalman Filter in Deformation Monitoring
The Extended Kalman Filter has been one of the most widely used methods for estimation of non-linear systems through the linearization of non-linear models. In recent several decades people have realized that there are a lot of constraints in application of the EKF for its hard implementation and intractability. In this paper a different estimation method is proposed, which takes advantage of the Sigma Point Transformation method thus approximating the true mean and variance more accurately. The new method can be applied to nonlinear systems without the linearization process necessary for the EKF, and it does not demand a Gaussian distribution of noise and whats more, its ease of implementation and more accurate estimation features enables it to demonstrate its good performance in the experiment of deformation monitoring. Numerical experiments show that the application of the Sigma Point Kalman Filter in deformation prediction is more effective than that of the EKF.
EKF nonlinear estimation Sigma Point Transform deformation monitoring
Wu Hongju Zhao Dongming
Department of Surveying Engineering Zhengzhou Institute of Surveying and Mapping Zhengzhou, China
国际会议
上海
英文
2536-2539
2011-07-26（万方平台首次上网日期，不代表论文的发表时间）