Research On Indoor Positioning And Route Planning Based On Smart Phone

Global Navigation Satellite System(GNSS)has been widely used in outdoor location services.In the indoor environment,it is difficult for GNSS to obtain accurate and reliable indoor positioning information due to building occlusion and multipath effects,which hinders navigation services to indoor locations.Expansion of service scenarios.Research on accurate,stable,and low-cost indoor positioning and navigation technologies can expand the application areas of indoor location services and provide key technical support for promoting the coordinated development of outdoor and indoor location services industries.This article focuses on the research of indoor positioning optimization technology and indoor path planning methods based on smartphones.The main research contents include:(1)In order to meet the positioning needs in the indoor navigation process,the indoor positioning module adopts PDR(Pedestrian Dead Reckoning,pedestrian dead reckoning)Program.In order to improve the cumulative error of the traditional PDR method in the continuous positioning process,a PDR modeling method based on multi-model fusion is proposed,and three traditional gait detection algorithms are incorporated in the gait detection stage,namely,peak detection algorithm,local maximum algorithm and advance Zero-crossing detection algorithm.At the same time,the Weinberg method and Kim method are combined in the step calculation stage.And the Kalman filter algorithm is used to correct the errors of gait detection and step length estimation.Experimental results show that the positioning error of the method proposed in this paper is 0.2844 ? 0.3911 meters in common scenarios,and it has high positioning accuracy.(2)In order to meet the path planning requirements in the indoor navigation system,a fusion scheme based on A* optimization algorithm and ant colony optimization algorithm is proposed.By improving the heuristic function of the A* algorithm,the search steps of the A*algorithm are reduced,and the pathfinding efficiency of the A* algorithm is improved.At the same time,the ant colony algorithm is introduced to further optimize the existing path.By setting the environmental penalty coefficient and increasing the pheromone concentration of the ant pathfinding area,the convergence speed of the algorithm is improved,and the ant colony algorithm is prevented from falling into the local optimum in the middle and late stages.The experimental results show that the method proposed in this paper reduces the total length of path planning by 14%,increases the convergence speed by 85%,and reduces the search time by 25%.(3)Built a smartphone-based Augmented Reality(AR)navigation system,using the proposed indoor PDR and path planning algorithms,and integrating the Apple ARKit framework.Through the test of building scenes,smartphone-based indoors can be realized.The navigation functions of positioning,path planning and AR help guide users to navigate from the initial point to the destination.