Adaptive Integrated Navigation Information Fusion Algorithm Based on Elman Network

2006 ◽  
Author(s):  
Yi Xiao ◽  
Guan Xin
Keyword(s):  
Information Fusion ◽  
Integrated Navigation ◽  
Elman Network ◽  
Fusion Algorithm ◽  
Navigation Information

scholarly journals Upper Stage Visual Inertial Integrated Navigation Method Based on Factor Graph

2021 ◽  
Vol 2085 (1) ◽  
pp. 012018
Author(s):  
Peng Wu ◽  
Rongjun Mu ◽  
Bingli Liu
Keyword(s):  
Information Fusion ◽  
Inertial Sensors ◽  
Joint Probability ◽  
Graph Model ◽  
Factor Graph ◽  
Joint Probability Distribution ◽  
Integrated Navigation ◽  
Fusion Algorithm ◽  
Upper Stage ◽  
Navigation Information

Abstract In the working process of the upper stage integrated navigation information fusion system, the multi-source navigation information fusion algorithm based on factor graph Bayesian estimation is used to fuse the information of inertial sensors, visual sensors and other sensors. The overall joint probability distribution of the system is described in the form of probability graph model with the dependence of local variables, so as to reduce the complexity of the system, adjust the data structure of information fusion to improve the efficiency of information fusion and smoothly switch the sensor configuration.

Study of DR/GPS Integrated Navigation on Nonlinear Adaptive Data Fusion Algorithm

2013 ◽  
Vol 823 ◽  
pp. 317-320
Author(s):  
Meng Long Cao ◽  
Shu Mei Yao
Keyword(s):  
Nonlinear System ◽  
Data Fusion ◽  
Information Fusion ◽  
Navigation System ◽  
State Vector ◽  
High Order ◽  
Experimental Results ◽  
Integrated Navigation ◽  
Fusion Algorithm ◽  
Integrated Navigation System

Aiming at collecting data fusion problem for the actual project integrated navigation system,this thesis propounds the system measured mathematics models and proposes adaptive information fusion algorithm based on nonlinear system. The proposed method considers system unmodelled part and high order item as the noise item and the state vector to coupled estimated,thus the sensitivity of the algorithm to the model is improved. The effect of the improved algorithm is tested by the simulation in the environment of Matlab. The experimental results demonstrate that this algorithm can improve the accuracy of the integrated navigation system, thus has the value of practice application.

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