The Factor Graph Information Fusion Algorithm With Time-varying Noise Estimate for All-Source Navigation System

2021 ◽  
Author(s):  
Yuyang Ge ◽  
Xinlong Wang
Keyword(s):  
Information Fusion ◽  
Navigation System ◽  
Factor Graph ◽  
Time Varying ◽  
Fusion Algorithm ◽  
Noise Estimate

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.

Aided Navigation System Research Based on Multi-Information Fusion

2012 ◽  
Vol 479-481 ◽  
pp. 207-212
Author(s):  
Xiao Hui Zhang ◽  
Liu Qing ◽  
Mu Li
Keyword(s):  
Information Fusion ◽  
Navigation System ◽  
Evidence Theory ◽  
Final Decision ◽  
Test Results ◽  
System Research ◽  
Fusion Algorithm ◽  
Distance Information ◽  
Radar Sensors ◽  
Vision Sensors

This paper designed a multi-information fusion algorithm after analysis information from vision sensors and radar sensors. This algorithm used D-S evidence theory to fuse the information of vision sensors and radar sensors to judge the front obstacles, and a final decision is made by the distance information provided by radar to decide whether give the driver corresponding warning. It also designed a critical vehicle distance, which can change according to relative distance and relative velocity. The test results show that this algorithm can give warning information correctly and greatly decrease the uncertainty, thus satisfying the requirement of car aided navigation system. At a resolution of 320×480, the identifying speed of this algorithm can reach 62.5ms/F which satisfied the requirement of real-time of car navigation.

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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