Research On Technologies Of Pedestrian Navigation Based On MEMS Inertial Devices

Pedestrian navigation technology based on MEMS inertial devices occupies an important position in the field of pedestrian navigation with its high degree of autonomy.The inertial pedestrian navigation system can achieve pedestrian positioning without relying on the signal transmission station,and can be widely used in various indoor and outdoor occasions.However,the problem of error accumulation over time in inertial navigation also exists in inertial pedestrian navigation.In view of this problem,inertial pedestrian navigation technology is studied.Pedestrian navigation algorithms need to use zero velocity update technology to suppress the accumulation of speed error over time,but traditional zero velocity update technology generally uses a preset threshold to judge the stationary phase,which will lead to misjudgment and incompleteness of the stationary phase.To improve the stationary phase judgment method.Choose a comprehensive angular velocity,acceleration data stationary phase judgment conditions,and to solve the problem of different pedestrians in pedestrian navigation and changing walking environment,designed an adaptive stationary phase judgment threshold acquisition method based on clustering algorithm.And according to the duration of the stationary phase and the swing phase,the time threshold is used to solve the problem of the discontinuousness of the stationary phase and the swing phase.Then,the problem that the attitude angle error during pedestrian navigation cannot be suppressed without input of external information is studied.In the design,the characteristics of the stationary phase angular velocity is zero and the law of pedestrian walking is adopted.The small change in heading angle at the end of gait is used as an extended Kalman filter observation to estimate the navigation error.Finally,to solve the problem that the trajectory appears glitches which affects the solution result when the speed is set to zero during position calculation,the extended Kalman filter is used to integrate a variety of inertial information in the stationary phase to estimate the navigation error and then the trajectory smoothing also suppresses the accumulation of errors over time,ensuring navigation accuracy.In this paper,the pedestrian navigation system algorithm based on the foot mounted inertial sensor is studied,and the field walking test is carried out,and the results of the pedestrian walking trajectory when using different error compensation methods are compared.Experiments show that the inertial pedestrian navigation algorithm designed in this paper has played a positive role in improving navigation accuracy.