WiFi Based Motion Positioning And Tracking System

Due to the rapid development of Internet of Things technology and various wireless communication technologies,nowadays people's demand for location-based services is also higher and higher,which makes the demand for location-based services,especially indoor location-based services is increasing and the requirements are also rising.Due to the development and popularization of Wi Fi technology,using Wi Fi to achieve positioning technology has always been a hot research in the field of positioning.Compared with the traditional RSSI,Wi Fi Channel State Information(CSI)has become a hot research in the field of Wi Fi positioning because it has more fine-grained information,better stability and more data.On the other hand,the traditional Wi Fi location is usually applied to the static scene,which limits the practical application of this technology.Therefore,the main goal of this paper is to design a scheme to locate the moving target.The specific work of this paper is as follows:(1)This paper designs and implements a location algorithm based on phase information in CSI.The algorithm can process the phase data in CSI,eliminate outliers and compensate offset to reduce the interference of external errors.Then,the algorithm calculates the phase value of the CSI subcarrier by using the differential method,so as to calculate the distance information and the angle of arrival information of the wireless signal transmitting device relative to the signal receiving device,and then obtain the relative position of the electromagnetic wave signal receiving end and the transmitting end.(2)In this paper,a trajectory tracking algorithm is designed and implemented by using Kalman Filter.Kalman Filter can not only track the moving target trajectory,but also suppress the positioning error of direct positioning results.Because the traditional Kalman Filter can hardly to deal with the problem of the mutation of human motion state in the test case,this paper proposes an improved Kalman Filter algorithm.The improved Kalman Filter algorithm can still work normally when the human motion state changes suddenly.But the algorithm will lead to the accuracy of trajectory tracking is reduced,so the algorithm is improved again.The accuracy of the twice improved Kalman Filter algorithm is improved.(3)In this paper,the program implementation and experimental analysis of the above positioning algorithm and trajectory tracking algorithm are carried out.In this paper,the system prototype is built on Linux platform,and the related program content is implemented in Open Wrt intelligent router system.Then,according to the simulation results,the corresponding test cases are proposed to test the algorithm function.The test results show that the algorithm can provide a positioning result with an average error of 0.5m when the person is in a static state.When the person is in linear motion,the Kalman filter algorithm can provide a positioning result with an error of 0.05 m.