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.

A Research on the Improved Information Fusion Algorithm

2014 ◽  
Vol 543-547 ◽  
pp. 1909-1912
Author(s):  
Guo Dong Zhang ◽  
Rui Min Qi
Keyword(s):  
Decision Making ◽  
Information Fusion ◽  
Evidence Theory ◽  
Source Information ◽  
Fusion Algorithm ◽  
Mutually Independent

In the field of information confusion, evidence theory takes advantage of its uncertainties. But in practical evidences are always mutually independent, However, multi-source information fusion is a comprehensive integration and then obtaining decision-making, sometimes the result of information fusion give us wrong conclusion. So an improved information fusion algorithm is proposed in this paper. It can heighten the information confusion reliability and accuracy in a practical example.

Information Fusion Algorithm for Electromechanical Equipment Based on DS Evidence Theory

2013 ◽  
Vol 380-384 ◽  
pp. 1125-1128 ◽  
Author(s):  
Yao Hui Zhang ◽  
Jun Xu ◽  
Kang Du
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
Prediction Method ◽  
Electrical Equipment ◽  
Fusion Algorithm ◽  
State Prediction ◽  
Level Information ◽  
The Difference ◽  
Equipment State ◽  
Electromechanical Equipment

According to the problem that the difference of test mode, mixed quantitative and qualitative information of electromechanical equipment state prediction, a state prediction method based on information fusion was proposed in this paper. It was used DS evidence theory to fuse decision level information of electromechanical equipments at this method. Simulation results showed that it is feasible and effective that information fusion technology is applied on the state prediction for mechanical and electrical equipment. Information for decision-making integrated repeatedly by different forecasting methods, can greatly reduce the blindness of judgment and improve the accuracy of state prediction.

The Application of Fusion Algorithm Based on Matrix Analysis in Evidence Theory

2014 ◽  
Vol 687-691 ◽  
pp. 1412-1415
Author(s):  
You Zhi Zhang ◽  
Yu Dong Qi ◽  
Han Li Wang
Keyword(s):  
Time Delay ◽  
Information Fusion ◽  
Evidence Theory ◽  
Matrix Analysis ◽  
Fusion Algorithm ◽  
C Language ◽  
Evidence Combination ◽  
Delay Increase ◽  
Recursive Calculation ◽  
Sensor Information

This paper directly adopts evidence reasoning formula to calculate sensor information fusion result. The amount of calculation and calculation time delay increase with the increasing number of target found, uses two recursive calculation ways of evidence combination to calculate results, and proposes a fusion algorithm based on matrix analysis, using matlab software and C language programming to realize the method and calculate by an example. The results prove that the fusion result calculated by the method gets the same result as that of evidence reasoning synthesis formula, but the time needed for calculation will be reduced.

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