Study On Indoor Positioning And Navigation Algorithms Based On The MEMS Inertial Devices And Smartphone

With the rapid development of industrial intelligent, and the development of inertial sensors and smart handheld devices is quickly with each passing day, the demand of people for the indoor environment location service that based on the smart handheld devices is becoming more and more urgent. Statistics show that the time people spent indoors accounted for over 80% of the total people activity time. In order to improve people's living quality and comfort, there is an urgent need in the indoor environment, especially in shopping malls, supermarkets and public entertainment places where should implement the indoor positioning and navigation functions. The location service based on indoor environment has a broad space for development and application prospect, it also has been one of the hot spots of scientific research in many institutions at home and abroad in recent years. This topic is the study on indoor positioning and navigation algorithms based on MEMS inertial device and smartphone electronic compass, and mainly includes the following content:(1) Analyzing and comparing the indoor positioning methods that developed rapidly and maturely, and analyzing the advantages and disadvantages of indoor positioning technology which based on inertial sensors. Determining the problems to be solved and the main research direction of indoor positioning system that based on the inertial navigation components.(2) Analyzing the basic navigation principle of strap-down inertial navigation system, and summing up and introducing the coordinate system which is commonly used and the transformation relations of the coordinate system, as well as the attitude algorithm and position calculating algorithm.(3) According to the characteristics of pedestrian movement, this paper designed the indoor positioning and navigation system which based on the combination of the MEMS inertial sensors and Smartphone electronic compass. The system obtains the pedestrian movement data through two kinds of data sampling method: one is hand-held Smartphone and the other is shoe-mounted inertial sensor. Finally, we can obtain two important navigation data: one is relatively accurate moving attitude data of pedestrian steps and the other is pedestrian movement course.(4) As accumulative error remains a problem in indoor positioning and navigation algorithm, this system filtering the sampled data through IIR filter firstly, and filtering out the vibration noise of pedestrian movement. Then correcting cumulative error which caused by the inertial navigation calculating through the zero velocity detection and correction algorithm which based on the threshold judgment condition of acceleration amplitude, acceleration variance and angular velocity amplitude, finally obtaining the accurate navigation location information.(5) Aiming at the pedestrian heading angle drift problem in inertial navigation calculating process, this paper designed the pedestrian heading angle fusion algorithm based on MEMS gyroscope and Smartphone electronic compass, correcting the pedestrian heading angle information. The Smartphone electronic compass can not output the accurate electronic compass data because of the influence of ambient magnetic field, so this paper uses the sliding mean filter algorithm to process the sample data.(6) Through the simulation experiment of the system algorithm with the MATLAB software, we verify the navigation precision and the feasibility of the system algorithms.(7) We set up the hardware platform of indoor positioning systems which based on MPU6050 inertial sensors, the Bluetooth module and Smartphone, and write the software of indoor positioning navigation system on Android software platform, to verify the application performance and real-time performance of the navigation algorithm.