INTEGRATED NAVIGATION ALGORITHM BASED ON FUZZY CONTROL

Abstract

The integrated navigation system that combines the global positioning system (GPS) and the inertial navigation system (INS) has attracted widespread attention. In order to improve its positioning and navigation accuracy, Kalman filtering algorithms are usually used to process navigation data. This paper combines fuzzy control theory with Kalman filter, and proposes an integrated navigation algorithm based on fuzzy control theory, specifically observing each component of the residual error, using multiple fuzzy inference systems to modify the measurement noise variance matrix to approximate the real noise characteristic. Through multiple simulation experiments, the results show that the algorithm can effectively suppress the filtering divergence.