A novel information fusion algorithm for GPS/INS navigation system

Author(s):  
Xiaochuan Zhao ◽  
Qingsheng Luo ◽  
Baoling Han ◽  
Xiyu Li
2012 ◽  
Vol 479-481 ◽  
pp. 207-212
Author(s):  
Xiao Hui Zhang ◽  
Liu Qing ◽  
Mu Li

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.


2013 ◽  
Vol 823 ◽  
pp. 317-320
Author(s):  
Meng Long Cao ◽  
Shu Mei Yao

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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