Research On Key Technologies Of Integrated Navigation For High-speed UAV

Aiming at the problems of low navigation accuracy and traditional Kalman filter's divergence during high-dynamic flight of high-speed unmanned aerial vehicles,this paper deeply studies the navigation algorithm which is suitable for high-dynamic flight environment to improve the anti-jamming capability and navigation accuracy of the integrated navigation system.The subsystems and sensors' measurement characteristics of the UAV navigation system during high-dynamic flight are analyzed.In the meantime,the coning error compensation algorithm and the height divergence problem are studied in depth.Finally,this paper researches the multi-sensor information fusion algorithm in high-dynamic environment,and proposes an integrated navigation information fusion algorithm of UAV with high adaptability,high robustness and high navigation accuracy.Simulation and experimental results show that the proposed algorithm has higher anti-interference ability and navigation accuracy than traditional integrated navigation algorithm.The main contents of this paper are as follows:(1)The measurement characteristics of the subsystems used in high-speed UAV integrated navigation system are analyzed,and the problems faced in UAV navigation are explored.Based on this,coning error compensation method,height direction complementary filtering scheme and information fusion algorithm with strong adaptability and high robustness are determined.(2)The research on the coning error compensation algorithm is carried out.The coning error compensation algorithm based on frequency series expansion is deduced in detail,and the coning error under different coning motion scenes is analyzed and compared.Based on this,a design method of coning error compensation algorithm based on device matching criterion is proposed,which provides a design reference for the coning error compensation algorithm in practical applications.Finally,the effectiveness and accuracy of the proposed coning compensation algorithm design method are verified by simulation.(3)The altitude channel algorithm of UAV is studied,and a two-stage complementary filtering algorithm based on vertical velocity and altitude is proposed.Experiments show that the algorithm can not only get high-dynamic quality information without time divergence,but also suppress vertical velocity drift(4)The SINS/GNSS integrated navigation information fusion algorithm in high-dynamic environment is studied.The adaptive estimation method of system noise variance matrix and measurement noise variance matrix,strong tracking filter and H filtering are deduced and analyzed in detail In the high-dynamic environment.Based on the idea of the three methods,a strong adaptive filtering information fusion algorithm is proposed.(5)Four simulation scenarios of high-dynamic environment are designed and the actual flight test was carried out.The navigation accuracy and anti-jamming ability of Kalman filter,strong tracking filter,H? filter and strong adaptive filter are compared respectively.And the paper proves that strong adaptive filter has a higher performance in high-speed UAV integrated navigation than other three methods.