| With more and more attention paid to indoor navigation,how to improve the accuracy of indoor navigation is the focus of indoor navigation technology research.Due to the coverage of various indoor obstructions,satellite navigation signals such as GPS and Bei Dou cannot be received,and other indoor navigation systems such as Wi-Fi cannot be used normally in the event of sudden disasters and modern wars.An indoor navigation method based on Inertial Measurement Unit(IMU)provides a better solution for indoor navigation when external signal sources such as GPS navigation sources are stoped.The IMU can measure the acceleration and heading information of the moving person,and then obtain the trajectory of the pedestrian indoors,so as to achieve the purpose of providing navigation and positioning function in the indoor scene.However,due to the defects of the IMU itself,long-time use will cause the track to diverge,causing errors to accumulate.Therefore,assisting with other signal sources on the basis of IMU has become a hot spot in indoor navigation research.This article uses Ultra-Wide Band(UWB)module to assist IMU inertial navigation equipment,and uses UWB's networking and communication functions to form multiple IMU inertial navigation measurement nodes into an autonomous cooperative network.At the same time,there is no need for external signals,only UWB ranging information and cooperative navigation technology are used to constrain the network to reduce the navigation and positioning errors of a single mobile node and the entire cooperative network,and ultimately improve the accuracy of navigation and positioning.Firstly,this thesis analyzes the IMU measurement method,and combines the IMU and strap-down inertial navigation,using strap-down inertial navigation quaternion method,the output of the IMU is more accurate initial attitude information and position information.At the same time,the reasons for the error of IMU are analyzed.In this system,since the value measured by UWB is a scalar,the accuracy of the network heading information is a very important factor.Therefore,this article adds a magnetometer to correct the heading output by the IMU,and uses Kalman filtering to process the IMU and the magnetometer to reduce the heading error.At the same time,the network communication function and ranging function of UWB are studied.UWB technology is used to combine multiple mobile nodes to form a collaborative network for the application of collaborative navigation technology.Secondly,the mathematical model of coordinated navigation and positioning data fusion is deduced and established,the state equation and observation equation of the system are established,then use the model to solve the navigation system.This paper studies whether the particle filter algorithm is fea sible,and on this basis,the Markov chain Monte Carlo method is added to improve the particle filter algorithm.Simultaneously,the mathematical model of the algorithm is simulated and the feasibility of the algorithm is verified.The trajectory reduction degree is used to judge the effectiveness of the algorithm.Finally,an experiment was designed to verify the correctness of the theory proposed in this article.The measurement system is composed of IMU and UWB,and the experiment is carried out in the actual indoor environment.The experimental results show that the accuracy of the IMU/UWB autonomous coordinated navigation and positioning after the addition of UWB assistance and improved particle filter algorithm processing is compared with that of the independent IMU inertial navigation When ?=1m,the accuracy of trajectory reduction is increased by 38.8%,and when ?=3m,the accuracy of trajectory reduction is increased by19.5%,which can effectively improve the accuracy of navigation and positioning. |
PDF Full Text Request