Ensemble Kalman filtering for nonlinear systems with multiple delayed measurements

Author(s):  
Yucheng Zhou ◽  
Jiahe Xu ◽  
Yuanwei Jing
Author(s):  
Xinmei Wang ◽  
Zhenzhu Liu ◽  
Feng Liu ◽  
Wei Liu ◽  
◽  
...  

Traditional unscented Kalman filtering (UKF) cannot solve the filtering problem for nonlinear systems with colored measurement noises and one-step randomly delayed measurements. To fix this problem, a new UKF algorithm is proposed in this paper. First, a system model with one-step randomly delayed measurements and colored measurement noises is established, wherein a first order Markov sequence model for whitening colored noises and an independently identical distributed Bernoulli variable for modeling one-step randomly delayed measurements is introduced. Second, an UKF is proposed for the above established models through unscented transformation by calculating the nonlinear states posterior mean and covariance based on the Bayesian filter framework. Specially, the proportional symmetric sampling method is used in the new UKF algorithm. Finally, the effectiveness and superiority of the proposed method is verified via simulation.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Sumanta Kumar Nanda ◽  
Guddu Kumar ◽  
Vimal Bhatia ◽  
Abhinoy Kumar Singh

2012 ◽  
Vol 48 (1) ◽  
Author(s):  
Liangping Li ◽  
Haiyan Zhou ◽  
Harrie-Jan Hendricks Franssen ◽  
J. Jaime Gómez-Hernández

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 78029-78036 ◽  
Author(s):  
Xiao-Liang Yang ◽  
Guo-Rong Liu ◽  
Nan-Hua Chen ◽  
Tai-Shan Lou

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