Research On Indoor Positioning Technology Of UWB/MEMS

In the contemporary era of mobile internet,the demand of location-aware application is increasing sharply.However,it is relatively mature for outdoor location based service(LBS)based on GNSS technology in the present situation.In the indoor environment,the satellite signal is vulnerable to keep out so that can't complete orientation.In order to satisfy the demands for indoor positioning,some experts and scholars on the systemic research on the photoelectric,sound,etc,and put forward ultrasonic,infrared,bluetooth and so on.And they have unique advantages,but there is no single positioning technology that can solve all the problem of indoor positioning.On the background,the paper systematically makes research on UWB positioning technology and MEMS positioning technology.According to the merits and demerits of the two positioning technologies,they are combined to realize positioning under complicated environment.The main contributions of this dissertation include:1.For the problem that the UWB signals are susceptible to the influence of multipath and non-line-of-sight(NLOS),this paper proposes a kind of positioning algorithm based on particle filter by the analysis of CHAN algorithm based on two steps of weighted least squares and least square algorithm with constrained conditions.Localization algorithm based on particle filter can effectively improve the outliers problem from UWB positioning caused by multipath and NLOS,and effectively reduce the multipath and NLOS on the result of positioning and improve the positioning accuracy and system stability.2.For the problem of inertial navigation positioning error accumulation in the process,study thoroughly on the positioning principle of inertial navigation system and pedestrian movement model characteristic.This paper puts forward the low-pass filter reducing noise and zero velocity correction solution.It effectively reduced the acceleration and angular velocity of errors caused by the invalid vibration that used Butterworth filter to process the raw data collected.On this basis,it is done by detecting zero speed point using different methods and then using kalman filter for error correction to improve the positioning accuracy.3.Thorough the characteristic of UWB and MEMS respective positioning,the paper designs to achieve MEMS aiding UWB positioning algorithm and positioning algorithm based on kalman filter.When the results of UWB positioning appear larger error or fail to position,it will rely on MEMS for positioning.While the positioning error of two positioning methods both in the setting threshold value range,it should be given respectively to the weights of UWB and MEMS and will be combination of them to improve the continuity of indoor positioning.On the basis of UWB and MEMS working respectively,using the output information of MEMS sensor establishes state equation and using the positioning information of UWB/MEMS establishes measurement equation.Through the kalman filter,it can feedback and correct MEMS information.UWB/MEMS can effectively make up the deficiencies in the process of localization and the positioning accuracy and stability are greatly improved.