Study On Indoor Location Algorithm Based On PDR And Geomagnetic

With the rapid development of location-based services,the demand for indoor positioning is increasing day by day.However,due to the blocking of building walls and the influence of indoor environment,the high-precision GPS positioning technology used for outdoor can not provide reliable positioning in indoor environment.At present,most technologies applicable to indoor positioning rely on external devices,including Wi-Fi,RFID,UWB,Bluetooth,etc.How to simplify the deployment of positioning devices while maintaining positioning accuracy is the current focus of research.In view of the widespread popularity of smart phones,this thesis adopts the method of integrating Pedestrian Dead Reckoning(PDR)and geomagnetic positioning to conduct indoor positioning research.In order to improve the positioning accuracy of PDR,a constrained step detection algorithm based on the traditional peak detection method is proposed,which judges the peak and trough of the acceleration change value at the front and back moments,combining periodicity,continuity,similarity and symmetry Constraint,effectively filter out invalid steps,and the accuracy rate is higher than 98%.At the same time,by studying and analyzing the existing step size estimation models,an improved Weinberg step size estimation model based on the change value of acceleration proposed in this thesis.Experiments show that the error of the improved step size model in this thesis is less than 1.23%.Finally,through the analysis of the advantages and disadvantages of using gyroscope and magnetometer alone to calculate the direction Angle,the Kalman filter algorithm is used to fuse gyroscope and magnetometer to estimate the course,and the digital map combined with particle filter method to solve the problem of "position through the wall".In order to solve the problem that global search matching is needed in geomagnetic matching in geomagnetic positioning,a hybrid matching method combining single point matching and sequence matching based on DTW is proposed for geomagnetic matching.Firstly,the single point method is used to collect the geomagnetic data,and then the double precision geomagnetic fingerprint reference library is constructed by the Krigin interpolation algorithm,and the mixed matching is carried out at last.In order to further improve the positioning accuracy,the indoor positioning algorithm based on PDR and geomagnetic fusion is proposed in this thesis,and the problems of PDR positioning error accumulation and geomagnetic matching long time and wide range are effectively solved by using PDR positioning results and geomagnetic mixing matching.Through experimental verification,under all kinds of circumstances,the positioning accuracy of the fusion positioning algorithm with 62%probability is lm,and the maximum positioning error is less than 1.5 m,which meets the daily indoor positioning needs.