Research And Implementation Technology Of Multi-source Signal Analysis And Integrated Navigation Syste

The error of MEMS inertial devices will increase rapidly after long-term use.GNSS navigation can operate stably for a long time but local information is easy to lose.The combination of the two can make up for the shortcomings,and the error can be corrected with the help of the precise height measurement capability of the barometric altimeter.Can better complete navigation and positioning tasks.Therefore,it is necessary to understand the various sensor signals and error characteristics used in the integrated navigation system,and to separate and calculate the accurate data from the measurement results,so that it can be easily applied to the navigation computer.This paper focuses on sensor signal characteristics,strapdown inertial navigation,initial alignment methods,and basic principles and applications of integrated navigation.It uses barometric altimeter and GNSS to assist strapdown inertial navigation systems based on MEMS devices and performs multi-source signal integrated navigation through federated filters.The main research contents are as follows:1.Focus on the application principles and signal characteristics of MEMS inertial devices,gradually clarify the characteristics of the signal noise model of inertial devices in static,high overload and vibration states,and thus clarify the internal algorithm principles of strapdown inertial navigation system,and aim at There is a solution to the divergence of the altitude channel,and it shows the signal and error characteristics of the barometric altimeter and GNSS.2.Various application methods of initial alignment are studied,analytical alignment,inertial alignment,and optimal estimation alignment methods are gradually analyzed,and the analytical alignment,inertial alignment,and alignment methods are simulated in the static state of the experiment.The velocity is the Kalman filter alignment of the observation and the Kalman filter alignment is the comparison of the observation.The accuracy comparison results show that the initial alignment method based on the optimal estimation method is more accurate than other alignment methods.3.The integrated navigation system based on strapdown inertial navigation/barometric altimeter/GNSS is constructed,and the federal filter is used to fuse the data of three kinds of sensors to calculate the optimal navigation and positioning parameters.At the same time,the full-state flight trajectory of long-term low-speed movement of the aircraft and the full-state flight trajectory of short-term high-speed movement of the projectile were designed,and the accuracy of attitude,speed and position were compared with the highly corrected inertial navigation system.The simulation results show that the inertial navigation/barometric altimeter/GNSS combination has greater advantages in the calculation of attitude,speed and position.4.Designed and drawn an inertial device analog signal acquisition board based on FPGA and ARM,using FPGA for inertial sensor data acquisition and data transmission with MCU,ARM is responsible for inertial sensor data data storage and host computer communication and other functions,follow-up and completion The static state data collection experiment and the random vibration state data collection experiment are carried out.Through the experimental data,the measured static and dynamic noise error analysis and evaluation of the inertial measurement unit have been completed.