Vehicle platform attitude estimation method based on adaptive Kalman filter and sliding window least squares

2020 ◽  
Vol 32 (3) ◽  
pp. 035007
Author(s):  
Jun Luo ◽  
Yongkun Fan ◽  
Ping Jiang ◽  
Zijian He ◽  
Peng Xu ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Least Squares ◽  
Estimation Method ◽  
Sliding Window ◽  
Attitude Estimation ◽  
Adaptive Kalman Filter ◽  
Vehicle Platform

scholarly journals Robust Adaptive Filter for Small Satellite Attitude Estimation Based on Magnetometer and Gyro

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Zhankui Zeng ◽  
Shijie Zhang ◽  
Yanjun Xing ◽  
Xibin Cao
Keyword(s):  
Kalman Filter ◽  
Attitude Estimation ◽  
Optimal Filtering ◽  
System State ◽  
Small Satellite ◽  
Adaptive Kalman Filter ◽  
Satellite Attitude ◽  
Observational Noise ◽  
Robust Adaptive ◽  
The Impact

Based on magnetometer and gyro measurement, a sequential scheme is proposed to determine the orbit and attitude of small satellite simultaneously. In order to reduce the impact of orbital errors on attitude estimation, a robust adaptive Kalman filter is developed. It uses a scale factor and an adaptive factor, which are constructed by Huber function and innovation sequence, respectively, to adjust the covariance matrix of system state and observational noise, change the weights of predicted and measured parameters, get suitable Kalman filter gain and approximate optimal filtering results. Numerical simulations are carried out and the proposed filter is approved to be robust for the noise disturbance and parameter uncertainty and can provide higher accuracy attitude estimation.

Attitude estimation using a Neuro-Fuzzy tuning based adaptive Kalman filter

2015 ◽  
Vol 29 (2) ◽  
pp. 479-488 ◽  
Author(s):  
Mariana N. Ibarra-Bonilla ◽  
P. Jorge Escamilla-Ambrosio ◽  
Juan Manuel Ramirez-Cortes
Keyword(s):  
Kalman Filter ◽  
Attitude Estimation ◽  
Adaptive Kalman Filter ◽  
Neuro Fuzzy

An Adaptive Kalman Filter for UAV Attitude Estimation

2019 ◽  
Author(s):  
Yang Luo ◽  
Guoliang Ye ◽  
Yongming Wu ◽  
Jianwen Guo ◽  
Jinglun Liang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Attitude Estimation ◽  
Adaptive Kalman Filter

Improvement of Attitude Estimation Using Modified Rodrigues Parameters and Intelligent Controller

2014 ◽  
Vol 556-562 ◽  
pp. 2279-2284
Author(s):  
Qiang Liu ◽  
Fu Yin Gao ◽  
Chang Gang Wang ◽  
Yu Han
Keyword(s):  
Kalman Filter ◽  
Computational Efficiency ◽  
Fuzzy Controller ◽  
Inertial Sensors ◽  
Estimation Method ◽  
Attitude Estimation ◽  
State Variables ◽  
Filter Model ◽  
Modified Rodrigues Parameters ◽  
Filter Tuning

The attitude estimation method of attitude heading reference system (AHRS) using an Extended Kalman Filter (EKF) with a filter tuning algorithm based on fuzzy controller is introduced.The AHRS uses inertial sensors and magnetometers to calculate its attitude. It is known that the attitude update using gyros are prone to diverge and hence the attitude error needs to compensate using accelerometers and magnetometers. In this paper, a Kalman filter model with a state variables represented by Modified Rodrigues Parameters (MRP) is presented to improve the computational efficiency and a model changing algorithm is used to make the filter more robust to acceleration and magnetic disturbances.If the AHRS measures any disturbances which are caused by movement of the vehicle, using fuzzy controller changes the filter gain .Simulation results show, EKF tuned by fuzzy controller is correct method that makes robust to disturbances more properly ,Rodrigues parameters can improve the computational efficiency..

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