Abridged Gaussian sum extended Kalman filter for nonlinear state estimation under non-Gaussian process uncertainties

2021 ◽  
Vol 155 ◽  
pp. 107534
Author(s):  
Mahshad Valipour ◽  
Luis A. Ricardez-Sandoval
Keyword(s):  
Kalman Filter ◽  
Gaussian Process ◽  
State Estimation ◽  
Extended Kalman Filter ◽  
Nonlinear State Estimation ◽  
Gaussian Sum ◽  
Non Gaussian ◽  
Nonlinear State

scholarly journals The Extended Kalman Filter for Nonlinear State Estimation in a U-loop Bioreactor

2019 ◽  
Author(s):  
Tobias K. S. Ritschel ◽  
Dimitri Boiroux ◽  
Marcus Krogh Nielsen ◽  
Jakob Kjobsted Huusom ◽  
Sten Bay Jorgensen ◽  
...  
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Extended Kalman Filter ◽  
Nonlinear State Estimation ◽  
Nonlinear State

Broyden’s update based extended Kalman Filter for nonlinear state estimation

2021 ◽  
Vol 105 ◽  
pp. 267-282
Author(s):  
Tathagata Mukherjee ◽  
Devyani Varshney ◽  
Krishna Kumar Kottakki ◽  
Mani Bhushan
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Extended Kalman Filter ◽  
Nonlinear State Estimation ◽  
Nonlinear State

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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