Attitude Estimation of the Multi-rotor UAV Based on Simplified Adaptive Kalman Filter Algorithm

Due to sensor accuracy and noise interference and other reasons, the measured data may be inaccurate or even wrong. This will reduce the accuracy of the filter and the reliability and response speed of the Kalman filter, and even make the Kalman filter lose the stability. In this paper, a new INS initial alignment error model and observation model are derived for the errors in INS initial alignment. The adaptive Kalman filter is built to improve the stability and the accuracy of filter. The specific method is to make the adaptive Kalman filter manage to correct the filter online by getting the observed data. The simulation results show the proposed algorithm improves the accuracy of initial alignment in SINS, and prove the adaptive Kalman filter is effective. The main innovation in this paper is to manage to build the adaptive Kalman filter to modify the filter online by using the observed data. The adaptive Kalman filter algorithm improves the accuracy of the filter.

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Research on adaptive Kalman filter algorithm based on fuzzy neural network

The 2010 IEEE International Conference on Information and Automation ◽

10.1109/icinfa.2010.5512237 ◽

2010 ◽

Cited By ~ 3

Author(s):

Zhen Shi ◽

Peng Yue ◽

Xiuzhi Wang

Keyword(s):

Neural Network ◽

Kalman Filter ◽

Fuzzy Neural Network ◽

Adaptive Kalman Filter ◽

Fuzzy Neural ◽

Kalman Filter Algorithm

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

Abstract and Applied Analysis ◽

10.1155/2014/159149 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 4

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.

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Detection of change in physiological measures using an adaptive Kalman filter algorithm.

Psychological Bulletin ◽

10.1037/0033-2909.96.3.581 ◽

1984 ◽

Vol 96 (3) ◽

pp. 581-588 ◽

Cited By ~ 6

Author(s):

Richard A. Heath

Keyword(s):

Kalman Filter ◽

Physiological Measures ◽

Adaptive Kalman Filter ◽

Kalman Filter Algorithm

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Application of Adaptive Kalman Filter Technique in Initial Alignment of Single-Axial Rotation Strap-Down Inertial Navigation System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.466-467.617 ◽

2012 ◽

Vol 466-467 ◽

pp. 617-621

Author(s):

Song Tian Shang ◽

Wen Shao Gao

Keyword(s):

Kalman Filter ◽

Axial Rotation ◽

Estimation Accuracy ◽

Initial Alignment ◽

Adaptive Kalman Filter ◽

Rotation System ◽

Kalman Filter Algorithm ◽

Axis Rotation ◽

Single Axis Rotation ◽

Better Than

In order to improve the accuracy of initial alignment which determines the accuracy of navigation, a Sage-Husa adaptive kalman filter algorithm is applied to SINS initial alignment of single-axis rotation system. The simulation result further shows that in the case of inaccurate statistical property of noise, the estimation accuracy of Sage-Husa adaptive kalman filter is better than the conventional kalman filter.

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