Application of an improved adaptive Kalman filter to transfer alignment of airborne missile INS

Author(s):  
Chun-ming Xie ◽  
Yan Zhao ◽  
Ji-nan Wang
2020 ◽  
Vol 20 (22) ◽  
pp. 13682-13693
Author(s):  
Geng Xu ◽  
Yulong Huang ◽  
Zhongxing Gao ◽  
Yonggang Zhang

2013 ◽  
Vol 62 (2) ◽  
pp. 251-265 ◽  
Author(s):  
Piotr J. Serkies ◽  
Krzysztof Szabat

Abstract In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman filter and adaptive state controller) is investigated in simulation and experimental tests.


Author(s):  
Lifei Zhang ◽  
Shaoping Wang ◽  
Maria Sergeevna Selezneva ◽  
Konstantin Avenirovich Neysipin

2012 ◽  
Vol 433-440 ◽  
pp. 2802-2807
Author(s):  
Ying Hong Han ◽  
Wan Chun Chen

For inertial navigation systems (INS) on moving base, transfer alignment is widely applied to initialize it. Three velocity plus attitude matching methods are compared. And Kalman filter is employed to evaluate the misalignment angle. Simulations under the same conditions show which scheme has excellent performance in precision and rapidness of estimations.


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