The Application Of Fuzzy Adaptive Information Fusion To Integrated Vehicle Navigation System

As an important aspect of Intelligent Transportation System, vehicle navigation system has great significance in many areas such as alleviating traffic, convenient for driving, transportation management, guard against theft and giving alarm, urgency asking for help. A key point of vehicle navigation system is to choose positioning way which aims to gain accurate and reliable information of vehicle location. GPS/DR integrated navigation way not only can solve the problem that solitary GPS is unable to positioning due to signal being shielded but also can restrain the cumulative error of DR effectively. Accuracy and reliability of navigation system are improved greatly, so this way has been adopted widely.However, for the sake of cost, cheaper DR sensors are adopted usually in GPS/DR integrated navigation system. So fusion algorithm is indispensable to improve the performance of whole system. That is how to fuse location information of GPS and DR effectively. Therefore, the key point of achieving GPS/DR integrated positioning is data fusion scheme, Kalman filtering is a good choice.Aim at the disadvantage of the traditional Kalman filtering, presents a novel method for integrated navigation based on fuzzy adaptive Kalman filtering. The noise' covariance of Kalman filtering is modified "online" by the fuzzy logic adaptive controller in order to module Kalman filtering to be optimal and to improve the positioning accuracy of the integrated navigation system.Besides mainly elaborates the integrated navigation algorithm, also analyzes the traditional federal Kalman filtering algorithm and presents the improvement of adaptive federal filter algorithm. Bring forward a bran-new information fusion arithmetic which is applied to central filter, information distribution coefficient algorithm based on dynamic comparison. The superiority of this algorithm is the theoretical simplicity and high processing speed and positioning precise. Obtain different weights of the all states estimate values that are based on the actual circumstance and fuse these values. Then the complicated calculation is avoided and precision is advanced. Ensures the high precision and good dynamic performance of the navigation system. By simulation on the computer, a series of localization data and simulation result confirm the feasibility and validity of this algorithm, and prove that the improved algorithm can enhance the precision and reliability of the vehicles positioning compared to the traditional algorithm.