A multi-sensor based federated kalman filter integrated navigation system

Abstract

A novel multi-sensor integrated navigation system is proposed in order to obtain better positioning information in complex environment for vehicle. The system utilizes Global Positioning System (GPS) and Inertial Navigation System (INS) for integrated navigation, using Kalman filters to fuse GPS and INS data. The optical flow sensor is composed of an image acquisition unit and an internal processing unit, and estimates the real-time speed of the object according to the optical flow method. In order to solve the problem of speed misalignment caused by the cumulative error of the INS in the case of GPS loss of lock, the optical flow sensor is introduced into the original integrated navigation system. On this basis, the information prediction and fusion process of these three sensors are discussed in depth, and the experiments of the integrated navigation system are carried out. The experimental results show that the system based on the innovative integrated navigation algorithm can more accurately control the vehicle speed and position, and improve the overall performance of vehicle navigation.