Research On Integrated Navigation System Based On BDS/SINS

With the continuous development of satellite navigation and positioning technology,navigation technology is widely used in people's daily life.At present,the world is committed to developing low-cost,high-precision navigation systems.In order to get rid of the excessive dependence on the US GPS navigation system,the research of the Beidou Satellite Navigation System(BDS)and the Strapdown Inertial Navigation System(SINS)integrated navigation technology has certain theoretical significance and application value to the promotion and application of BDS in military and civilian aspects.Based on the Beidou satellite navigation system(BDS)and the strapdown inertial navigation system(SINS),this research analyzes the strap update algorithm of SINS,the single point positioning algorithm of BDS,and the information fusion technology of the BDS/SINS integrated navigation.Using by simulation trajectories,the simulation analysis of these models proves its effectiveness and practicability.The main researches of this paper are as follows:Firstly,a brief overview of the current research status of GNS/SINS integrated navigation at home and abroad,and the common coordinate system and working principle of SINS.The attitude update algorithm based on equivalent rotation vector is studied,combined with the corresponding differential equations,the SINS algorithm is derived.The simulation experiment with Matlab proves that the solution error of the strapdown inertial navigation system accumulates with time.Secondly,the Beidou satellite navigation system is briefly described,and the common error sources of the BDS and the corresponding correction methods are analyzed.This paper focuses on the analysis and research of the Beidou satellite orbit calculation method and the algorithm of using the pseudorange and pseudorange rate to locate and measure the velocity.Using the navigation data received by the BDS base station,the accuracy of static pseudo-single single-point positioning is analyzed by Matlab simulation.The results show that the positioning error of BDS is much smaller than the positioning error of SINS,which provides a theoretical basis for the error of using BDS to modify SINS in integrated navigation.Thirdly,aiming at the shortcomings of excessive dependence of the traditional Kalman filter algorithm on the integrated navigation system model and the noise characteristics,the paper combines the attenuation factor adaptive algorithm and the noise weighted adaptive algorithm to propose the Kalman algorithm in BDS/SINS integrated navigation.The improved Kalman algorithm is compared with the traditional Kalman algorithm in the integrated navigation system by Matlab.The results show that the improved algorithm is superior to the traditional Kalman filter algorithm and improves the filtering accuracy.Fourthly,aiming at the problem of the precision drop of the integrated navigation system during the loss of lock in Beidou,this study designs a scheme of auxiliary integrated navigation based on radial basis function neural network.During the validity of the BDS signal,the RBFNN's powerful nonlinear fitting ability can be used not only the relationship between the gyroscope and the SINS position and velocity error,but also the relationship between the accelerometer and the SINS position and velocity error.The model is simulated by Matlab.The results show that the error in the speed and position of the integrated navigation system assisted by RBFNN is improved.Finally,the multi-sensor integrated navigation system for BDS/SINS may cause faults in navigation accuracy,and the Kalman filter is divergent,this research design the federal Kalman fault-tolerant structure.When it is detected that the system is faulty,the RBFNN is used to predict the satellite measurement data,and the predicted data is used instead of the BDS data to reconstruct the system.The simulation shows that the method has certain fault tolerance and fault handling capabilities.