Research On Key Technologies Of Precise Location For BDS/INS Integrated Navigation

Beidou satellite navigation system(BDS)is a global satellite navigation system independently built and operated by China,which is widely used in various industries.Inertial navigation system(INS)occupies a certain position in daily life due to its good dynamic response characteristics and non-interference.Composite navigation is a technology that combines the advantages of two or more systems.Its essence is complementary advantages.Filtering algorithm plays an important role in integrated navigation system.The traditional kalman filter is most widely used in navigation system,but the algorithm can only get the best filtering effect in linear system,and the system model and measurement model are very determined.However,in practical engineering application,it is difficult to meet these conditions.Based on inertial navigation fusion,a PID adaptive kalman filter algorithm is proposed in this paper.Firstly,the real-time Angle values of accelerometer and gyro are fused,and the PID controller is used to suppress the error fluctuation as the measured data,and the gyro data as the state data.Then through the filter equation with adaptive coefficient,combined with the data,the detailed theoretical analysis process is given,and finally the credible attitude positioning information is obtained.Experimental results show that the new algorithm can improve the kalman filtering algorithm.This paper studies the beidou satellite navigation system(BDS)/strapdown inertial navigation system(INS)integrated navigation system,to solve the problem of information,such as position and speed of an improved Sage-Husa adaptive filtering algorithm,overcame the filtering divergence problem in the traditional algorithm and can be achieved for the carrier of the combination of position and speed information.This algorithm can improve the accuracy of filtering through the form of adjustment factor under the condition that the statistical characteristics of system noise Q or measured noise R are unknown,and improve the disadvantages of the commonly used Sage-Husa algorithm,such as too much calculation and inaccurate estimation model.At the same time,a hardware platform for the collection of longitude,latitude and height is built.Experimental results show that the improved Sage-Husa adaptive filtering algorithm is more accurate than Sage-Husa filtering algorithm and attenuation and speed filtering algorithm.