scholarly journals State estimation based on nonlinear Kalman filter for fluid systems described by Burgers’ equation

2021 ◽  
Vol 87 (901) ◽  
pp. 21-00061-21-00061
Author(s):  
Takashi SHIMIZU ◽  
Tomoaki HASHIMOTO
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Burgers Equation ◽  
Fluid Systems ◽  
Nonlinear Kalman Filter

State Estimation of Vehicle’s Dynamic Stability Based on the Nonlinear Kalman Filter

2018 ◽  
Vol 1 (3) ◽  
pp. 281-289 ◽  
Author(s):  
Xiaofei Pei ◽  
Xu Hu ◽  
Wei Liu ◽  
Zhenfu Chen ◽  
Bo Yang
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Dynamic Stability ◽  
Nonlinear Kalman Filter

Diffusion nonlinear Kalman filter with intermittent observations

2017 ◽  
Vol 232 (15) ◽  
pp. 2775-2783 ◽  
Author(s):  
Guoqing Wang ◽  
Ning Li ◽  
Yonggang Zhang
Keyword(s):  
Kalman Filter ◽  
Sensor Networks ◽  
State Estimation ◽  
Target Tracking ◽  
Estimation Accuracy ◽  
Nonlinear State Estimation ◽  
Information Filter ◽  
Cubature Kalman Filter ◽  
Nonlinear Kalman Filter ◽  
Nonlinear State

In this article, we consider the distributed nonlinear state estimation over sensor networks under the diffusion Kalman filter paradigm, where data only exchanges among the neighbourhoods of sensors. We first obtain a novel nonlinear Kalman filter with intermittent observations based on cubature Kalman filter. After that, its equivalent information filter is derived, and the proposed diffusion cubature Kalman filter with intermittent observations is designed based on this information filter. The effectiveness of proposed algorithms is demonstrated by a typical target tracking example, and our algorithm has similar estimation accuracy when comparing with existing algorithms while consuming less computation and communication resources.

A Strong Tracking Cubature Kalman Filter for Nonlinear Estimation

2013 ◽  
Vol 313-314 ◽  
pp. 1115-1119
Author(s):  
Yong Qi Wang ◽  
Feng Yang ◽  
Yan Liang ◽  
Quan Pan
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Scaling Factor ◽  
Estimation Accuracy ◽  
Nonlinear State Estimation ◽  
Cubature Kalman Filter ◽  
Novel Method ◽  
Simulation Results ◽  
Tracking Filter ◽  
Nonlinear State

In this paper, a novel method based on cubature Kalman filter (CKF) and strong tracking filter (STF) has been proposed for nonlinear state estimation problem. The proposed method is named as strong tracking cubature Kalman filter (STCKF). In the STCKF, a scaling factor derived from STF is added and it can be tuned online to adjust the filtering gain accordingly. Simulation results indicate STCKF outperforms over EKF and CKF in state estimation accuracy.

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