Research On Indoor Location Technology Based On Map Information Constraint

In recent years,with the rapid development of information technology and the popularization of intelligent terminals,indoor positioning technology has gradually become a research hotspot,and there is a huge market demand worldwide.At present,the positioning system based on smart phones mostly uses PDR positioning as the main body.However,PDR positioning has error accumulation problems.Map information is an important auxiliary information in indoor positioning.It can display the positioning results and can also be used as auxiliary information to constrain positioning.Therefore,indoor positioning technology based on map information constraints has important research value.In this paper,based on the spatial information,structural map information and trajectory map information as constraint information,the PDR positioning technology and WiFi positioning technology are researched,and the PDR / WiFi fusion positioning algorithm based on map information is researched.First,the single PDR positioning and WiFi positioning are constrained by indoor space information,respectively.Aiming at the problem of not being able to adapt step counting at different speeds in PDR positioning and the error accumulation problem of PDR itself,an adaptive threshold gait detection method is proposed to improve the accuracy of step counting at different speeds,and using indoor space information for single PDR positioning constraint.Match the positioning results with preset information bases such as corners,WiFi semantic information,and wall line information to correct errors and heading in PDR positioning.Aiming at the problem of result jump in WiFi positioning in a large-scale positioning,the spatial information is used to divide the area,and a motion constraint method is proposed to limit the next positioning reference point in the corridor area to prevent positioning jump,and the distance constraint is used to adapt the WKNN algorithm Value of K.Then,considering the problem of positioning through walls and improving the overall positioning effect,the particle filter algorithm is used to fuse map information and PDR / WiFi for map-assisted positioning.The vector information of the space wall line is directly identified from the original map to determine the positional relationship between the particles and the non-conformance is removed.Conditional particles;incorporate semantic information as an observation into particle filtering to perform particle weight constraints instead of direct constraints during single PDR positioning.Aiming at the problem that the traditional particle filter algorithm sampling does not consider the observation information,the dual importance particle filter algorithm is applied to map-assisted indoor positioning;the self-recovery mechanism is designed for the problem of the destruction of the entire particle wall.Finally,aiming to improve user experience and further improve accuracy,the use of trajectory maps for map matching further constrains the trajectory after map assistance.For the corridor area,the point-to-arc topology matching method is used to project the trajectory points onto the preset trajectory map.For open spaces,on the premise of the purpose of walking,a virtual link algorithm combined with a virtual track algorithm is used for map matching.Finally,the positioning algorithm based on the overall constraint of map information has been experimentally verified.The average accuracy of the PDR / WiFi fusion map information positioning algorithm or PDR direct fusion map information positioning algorithm is within 1.7m,and the positioning track user experience is better.There will be no abnormal situations such as pedestrians passing through walls.Indoor positioning scheme design based on map information constraints has been completed,which can meet the needs of indoor positioning accuracy based on smart phones.The algorithm can be transplanted to smart phones for indoor positioning software development.