Research on multi-sensor information fusion system application for UAVS with long range and high altitude

Abstract

Multi-sensors combination is an effective means to improve the accuracy and fault tolerance of the navigation system for UAVs with long range and high altitude. Based on analyses of attitude determination using STAR sensor, this paper presents a SINS/STAR/GPS information fusion navigation system. To solve the problem of the incoordinate interval characteristics of multi-sensors, an asynchronous centralized Kalman Filter (AKF) is designed., and the filter period is divided to time update period and measurement update period. An extrapolation method is designed to deal with GPS information. Moreover, a new model is designed to solve the problem of attitude combination in process of vertical mobility. Simulation results indicate that filtering accuracy is improved by 50% with the Kalman Filter, and the method is of important value in engineering application