Research On Navigation Control And Tracking Technology Of Multi-rotor UAV Based On Kalman Filter

Due to its flexible maneuverability,simple mechanical structure and low production cost,multi-rotor UAV has great practical value and wide application prospects in aerial photography,agricultural plant protection,environmental monitoring,power patrol,express delivery,target tracking and other fields.Therefore,the research on multi-rotor UAV is one of the research hotspots of many scholars at home and abroad.This thesis has carried out research work on the integrated navigation technology,control technology and target tracking technology of multi-rotor UAV.In the aspect of UAV combined navigation,the establishment of precise navigation system model and high-precision multi-source information fusion algorithm are two core problems.Because of its non-linearity,strong coupling and under-actuation,UAV control needs to design an efficient and stable control system.The target tracking of the drone is mainly faced with the measurement deviation of the sensor.These deviations will seriously affect the accuracy of the target tracking and even lose the target.This thesis has studied the above issues:(1)In order to realize the navigation control of the drone,it is first necessary to establish an accurate mathematical model.This thesis briefly introduces the motion principle of the four-rotor UAV,analyzes the force of the UAV,and establishes the dynamic model of the four-rotor UAV.At the same time,the characteristics of the UAV are analyzed,and the navigation system models of the three UAVs are studied.(2)For the model uncertainty in the GPS/INS integrated navigation system of the UAV and the uncertain parameters(biases)of the system,this thesis introduces the statistical information of the uncertain parameters into the extended Consider Kalman filtering algorithm,and Based on the strong tracking method,a strong tracking extended Consider Kalman filtering algorithm is proposed.The simulation results of MATLAB show that the proposed algorithm can effectively reduce the adverse effects of model uncertainty and measurement bias on GPS/INS integrated navigation system,and effectively improve the navigation accuracy and stability of the entire navigation system.(3)In order to make the motion of the quadrotor UAV reach the ideal state,the dynamic model transfer function of the quadrotor UAV is designed,and the PID control system of the quadrotor UAV based on Kalman filter is studied.The control simulation system of the quadrotor UAV was established by MATLAB/Simulink,and the parameters of the PID control were set.The simulation results show that the PID controller based on Kalman filter effectively reduces the noise interference and improves the performance of the control.(4)For the problem of the unknown system deviation in the measurement information of the airborne radar when the multi-rotor UAV is tracking the target.In this thesis,an incremental measurement equation is established,and the general ICDKF algorithm and the additive ICDKF algorithm are proposed.The simulation results show that the proposed algorithm can effectively reduce the adverse effects caused by the measurement deviation in maneuvering target tracking and improve the target tracking accuracy.