Three Dimensional Trajectory Monitoring Based On Android Platform

As "the last kilometer" of the navigation system,the indoor positioning is always the hottest spot of the mobile Internet,and the demand from people for this location service is urgent.However,because of the complexity of indoor environment,the variable pattern,many kinds of interference and the block of buildings,the navigation method based on satellite is difficult to apply on the indoor positioning,the theory of errors and the indoor complex environment mechanism of action can’t be solved efficiently.Indoor positioning is largely need in military pedestrian system,firefighting and large venues.Since the GNSS navigation will lead to the problem of attenuation,multipath and other issues,and the indoor positioning technology based on base station has the status of high cost and poor autonomy,the Personal Dead-reckoning navigation based on low-cost MEMS inertial sensors become a hot topic in the field.After the research of this field and analyzing the indoor positioning experiment,in this paper,an algorithm of pedestrian autonomous positioning is designed and the algorithm is used to solve pedestrian location in real time based on the strapdown inertial navigation system.The system module is worn on the pedestrian foot,which can complete the pedestrian location in the indoor environment and display the track in the 3D model of the Android mobile terminal.Specifically the main work done in this paper are the following aspects.First of all,according to the requirement of precision,real-time and size of the indoor pedestrian location system,this paper introduces a complete design of the pedestrian autonomous positioning system.Secondly,by analyzing the gait features of pedestrians,the walking stage of pedestrian is divided into the static and non-stationary interval.The generalized likelihood ratio test is proposed to detect the pedestrian zero-speed interval,which can improve the accuracy of detection and lay a good foundation for the zero velocity correction algorithm.The attitude updating algorithm based on gradient descent which integrated the information of accelerometer,gyroscope and magnetometer is adopted to update the pedestrian attitude.Compared with the Kalman filter fused with multi-sensor information method,this algorithm obtains better fusion performance with less computation amount and lower sampling frequency,which provides us with a powerful condition for realizing the real-time system.The strength of the system lies in the use of a technique known as “Zero Velocity Update”(ZUPT)which almost eliminates the ill-effects of drift in the accelerometers.It works very well with different gaits,such as normal walking,running,up and down stairs.Then,the development of 3D display model based on Android mobile end,the deign of UI,the edition of logic code and the generation of application procedure could help us show the internal structure of the target building and receive the coordinate information from the autonomic location model so that it could show the track of pedestrian in depth.Finally,the experiment according to the indoor environment analyzes and verifies the correctness and feasibility of pedestrian autonomous localization algorithm,and the thesis realizes the real-time collection and decoding sensor information and display the consequence on the 3D model of mobile terminal.