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

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.

2012 ◽  
Vol 232 ◽  
pp. 205-209
Author(s):  
Yan Ren ◽  
Duan Xu ◽  
Wei Feng Yue

The problem of data fusion based on filter is studied for an integrated inertial navigation system / Beidou navigation system / global positioning system (INS/BNS/GPS) with uncertain noise and conditionality of using GPS. The integrated navigation system can be divided into two integrated navigation subsystems (INS/BNS and INS/GPS). The signals from GPS and BNS receivers are easy to be disturbed, so filter is used to estimate the subsystem errors which are transmitted to fusion center online. Then data fusion is carried out by using the fuzzy fusion algorithm. Simulation results show that the algorithm can improve the accuracy and stability of navigation system.


2012 ◽  
Vol 220-223 ◽  
pp. 2280-2283
Author(s):  
You Yi Ye ◽  
Xiang Zhao

This document explains how to aim at low-precision in navigation and position of Inertial Navigation System and dependence of Global Positioning System. A combination of these two systems provides good compensations for each other. GPS/INS integrated navigation system in high dynamic environment is studied, an integrated algorithm based on the pseudo-range and pseudo-range rate is introduced. By analyzing the error model of INS and GPS navigation systems, the state equation and the observation equation are founded. Finally, data fusion algorithm is simulated using kalman filtering algorithm, simulation results show that the data fusion algorithm can improve reliability and maturity of integrated navigation system.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Yuan Xu ◽  
Xiyuan Chen ◽  
Qinghua Li

As the core of the integrated navigation system, the data fusion algorithm should be designed seriously. In order to improve the accuracy of data fusion, this work proposed an adaptive iterated extended Kalman (AIEKF) which used the noise statistics estimator in the iterated extended Kalman (IEKF), and then AIEKF is used to deal with the nonlinear problem in the inertial navigation systems (INS)/wireless sensors networks (WSNs)-integrated navigation system. Practical test has been done to evaluate the performance of the proposed method. The results show that the proposed method is effective to reduce the mean root-mean-square error (RMSE) of position by about 92.53%, 67.93%, 55.97%, and 30.09% compared with the INS only, WSN, EKF, and IEKF.


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