Research On Multi-sensor Information Fusion Algorithm For Multi-rotor Aircraft

With the development of microprocessors,sensors,motors and attitude analysis methods and control algorithms,the research and development of multi-rotor aircraft has been paid more and more attention by researchers.How to get a relatively accurate flight data of the aircraft,so as to better control the flight of the aircraft is one of its core content,which also directly affects the multi-rotor aircraft system performance and application.This paper analyzes and studies the principles of the gyroscopes,accelerometers,magnetometers,GPS,barometer and laser range finder needed for the measurement of the flight status of multi-rotor aircraft,and their relationship with each other,according to their possible the error is modeled by the corresponding error.According to the characteristics of sensor output,the attitude angle,height,position and velocity information of multi-rotor aircraft are calculated.Aiming at the fact that a single sensor can not accurately give the current flight status of the aircraft,the information fusion algorithm model is established for the mathematical solution of several related sensors.A centralized Kalman filter model based on homologous sensor is established.The multi-sensor is modeled by the distributed Kalman filter process,and the sub-filter and the main filter are designed respectively.The improved Kalman filter algorithm is proposed by contrast analysis,and an improved federated Kalman filter framework is constructed and the key filtering of the key function is improved.The measurement accuracy of the low cost sensor is improved.In this paper,the classical Kalman filter,the decentralized federated Kalman filter and the improved federated Kalman filter effect are simulated and simulated respectively.The filtering effect is analyzed and discussed.The simulation results show that the improved federated Kalman filter The algorithm improves the accuracy of flight measurement,validates the effectiveness of the improved algorithm,and improves the flight stability and reliability of the aircraft.