Research On Indoor Navigation Technology Of Multi-sensor Fusion

Indoor navigation technology occupies a space for one person in the rapid development of today's society,It has become increasingly important in our lives,Inertial navigation technology because of its advantages of autonomy can easily implement in the indoor indoor positioning and navigation without device presets in the harsh environment that the signal is weak and the obstacles many.AS the core components in the system,MEMS(micro-electro-mechanical system)inertial devices choose ADIS16405,which integrated gyroscope and accelerometer,assisted by odometer,geomagnetic sensors,through the integration of data from multiple sensors,then we made a low-cost micro-navigation system to meet the needs of indoor navigation and positioning.The main work of this paper is:(1)The design and implementation of hardware platform.The system is mainly divided into two parts,one is the inertial navigation system(main system),the other is the inertial assistant system(secondary system).ARM is the navigation computer of the main system,equipped with inertial sensors,according to the characteristics of the sensors to design processing and interface circuit;The secondary system choose FPGA for processor,equipped with auxiliary sensors,data collects and processes through the Verilog language then transports to the main system through the serial port for data integration.Also includes the system structure,the design of power circuit.(2)The analysis and compensation of sensors.Firstly,to calibration MEMS gyro and accelerometer,we get the parameters of error model through indoor experiment,and we conducted the Allan variance and the nonlinearity analysis experiment for the MEMS sensors.Then,according to the error model of geomagnetic sensor,we calculated the parameters of ellipsoid model.Finally,we do the accurate calibration for speedometers through GPS signal outdoor.(3)The realization of the sensor fusion algorithm.MEMS inertial navigation system(MINS)error of integral internal will bring increased with the passage of time,in order to get the real time navigation information system,we need to use other sensors of velocity and position correction.We establish a combination filter model of the system and give the specific implementation method of EKF filtering algorithm,which is the main method of data fusion.Furthermore,in order to prevent the speed error caused by odometer,we use numbers of odometers to get multi signals integrate through fuzzy logic or neural network.(4)System test.After the completion of the actual system After the completion of the actual system,we do some tests to verify its actual operation,including the navigation and location,experiments are divided into two types of static and dynamic.The results is:after initial alignment,the horizontal attitude error and the heading attitude errorare less than 0.2°and 0.5°,under the turntable test,the horizontal attitude error are less than 0.4°in static test,the horizontal attitude error are less than 0.5 ° in dynamic test.The localization experiment results are shown in chapter sixth.