Research On Indoor Positioning Technology Based On Geographic Information Fusion

With the increasing demand for indoor positioning,the indoor positioning technology has become the focus of research at present.It has emerged a variety of indoor positioning solutions.Among them,inertial sensor-based strapdown inertial navigation system(INS)does not rely on external signal sources,and the cost is relatively low,making it the most suitable for a wide range of promotion.However,its positioning accuracy is often limited by the accuracy of the sensor.Positioning error usually accumulate over time,making it difficult to achieve stable positioning under long-term use.To solve the problems with inertial navigation systems,this paper realizes an indoor positioning technology based on geographic information fusion.We make use of magnetic field's direction information for inertial navigation system heading correction and design a particle filter that highly integrated with map information to improve positioning accuracy and stability of inertial navigation systems.The problem of heading angle drift has always been the key to the positioning accuracy.In this paper,a method of correcting the heading of INS using magnetic field's direction is proposed.By evaluating the disturbance of the current magnetic field and then the Kalman filter is used to fuse the effective magnetic field with the INS's heading.The method effectively suppresses the accumulation of heading angle errors in the positioning system and can prevent erroneous correction caused by a magnetic field with severe interference.The map in the indoor environment contains a lot of useful information,which is very helpful for improving the positioning accuracy.In this paper,a particle filter based on map constraint is designed,which make good use the map information.The constraint of the wall and the correction of the special position(stair/elevator,doorway,intersection,etc.)are effectively fused with the traditional INS.The optimal estimation under map constraint are made for achieving higher accuracy and robustness of positioning.In order to analyze the performance of the proposed methods,experiments for each method and complete system were conducted.The experimental results show that the indoor positioning technology based on geographic information fusion proposed in this paper can effectively eliminate the cumulative error of the heading and still maintain a high precision stably in a long time of experiment.The proposed method can effectively improve the positioning accuracy and stability of INS.It has good application prospect and value in positioning and navigation in complex indoor environments such as shopping malls,underground garages and so on.