Fuzzy Information Fusion Based on Genetic Algorithm for Vehicle Navigation System

In this paper, it is established the numerical model of federal Kalman filtering based on vehicle GPS/DR integrated location system. In order to resolve the shortcoming of the traditional federal Kalman filtering, a new method is presented in which the fuzzy logic system is combined with the traditional Kalman technology. This method can modify the statistical characteristic of noises on real time. It can not only modify the local filter but also bring forward a bran-new information fusion arithmetic which is applied to central filter. A fuzzy logic system is built to obtain different weights of the all states estimate values that are based on the actual circumstance and fuse these values. The acquisition of control rules and membership function of fuzzy controller usually rely to a great extent on empirical and heuristic knowledge. In this paper, genetic algorithm is used to optimize fuzzy logic controller and obtain the optimal or sub-optimal control rules. The result of simulation and road test indicates that it is useful with high effectiveness and practical.