Researches On Indoor Positioning Technology Based On Bluetooth And Inertial Sensor

With the advent of the Mobile Internet Era,sales of mobile smart devices(such as smartphones)are outpacing sales of traditional desktop computers.This increase in Mobile Intelligent Terminal devices has spurred the exploration of position awareness and its application scenarios.The use of indoor positioning technology to provide indoor location services has become a major important issues in the field of Location Based Service(LBS).However,the existing indoor positioning technology in the practical and positioning accuracy is still insufficient.Based on the inertial sensor positioning algorithm and the advantages of Bluetooth positioning algorithm,a fusion algorithm of inertial sensor and Bluetooth location algorithm based on extended Kalman Filter is proposed in this paper.The indoor positioning system is developed according to the actual situation.The work of this paper mainly includes the following points:(1)Most of the existing PDR algorithms are based on the geographic coordinate system,while the sensor data is based on the carrier coordinate system.Therefore,this paper presents an attitude algorithm based on Mahony complementary filtering algorithm,and then studies the step detection algorithm,stride length estimation and direction estimation on the basis of attitude algorithm.For the step detection algorithm,this paper puts forward the high frequency and low frequency filtering of z-axis acceleration to eliminate the noise,and improves the step accuracy by threshold detection.For stride length estimation,this paper presents a nonlinear step size model.Bluetooth location technology is mainly based on triangulation method and indoor path loss model.This article analyzes the current trilateration algorithm and the indoor path loss model by reading a large amount of literature,and gives the solution method of triangulation measurement and the equation of indoor path loss model.In addition,for indoor path loss model,two calibration techniques are proposed to improve the positioning accuracy of Bluetooth.(2)The inertial sensor location algorithm is prone to accumulate errors,and Bluetooth positioning algorithms tend to fluctuate by the noise interference.In this paper,based on the characteristics of two algorithms,an inertial sensor location algorithm and a Bluetooth location algorithm fusion algorithm based on Kalman Filter are proposed.Firstly,the framework of the fusion algorithm is established,then a suitable extended Kalman filter algorithm is selected.At last,the superiority of the fusion algorithm is proved through theoretical verification and experimental verification.(3)In order to verify the practicability of this algorithm,the indoor positioning system is developed.The system includes a mobile terminal and a server.The mobile terminal is developed on the smartphone based on Android system,including inertial sensor positioning,Bluetooth positioning,communication module,and user interaction module.The server is developed on the Flask platform based on Python,including user authentication interaction modules,data management modules,etc.