Research On The Sequence Matching Magnetic/ PDR Fusion Localization Algorithm

At present,the existing navigation system based on single positioning method can basically meet the requirements of location estimation and path selection,but it needs to deploy a large number of positioning beacons,which has strong dependence on equipment and is difficult to benefit from indoor scenes with insufficient infrastructure.Under the premise of no additional facilities,it is worthwhile to study indoor highprecision positioning based on portable device.All indoor positioning technologies,methods for achieving pedestrian position estimation in mobile terminals include visual positioning,magnetic localization,and pedestrian dead reckoning.The processing of visual positioning is difficult to realize real-time performance.The pedestrian dead reckoning technology can achieve accurate location in short time but has accumulation errors.The magnetic positioning has advantage of high accuracy.However,the matching calculation consuming much time.Therefore,a magnetic/PDR fusion localization algorithm based on particle filter is designed to achieve high-precision pedestrian location.The research content of this paper mainly includes:(1)We exploring the spatial difference and stability of indoor geomagnetic field proved that the geomagnetic feature can be used as fingerprint.Because of complex internal electromagnetic environment in smartphone and diversity of user behaviors,it is difficult to obtain the presion geomagnetic signal.Firstly,we calibarate the magnertometer of smartphone;we process using moving average Wavelet denoising,Savit Ky-Golay and Butterworth filtering to optimize the original geomagnetic signal.(2)We explain the advantages and disadvantages of path continuous and grid single point geomagnetic signal acquisition methods.The continuous acquisition method is used to construct the two-dimensional geomagnetic signal map based on nearest neighbor,inverse distance weighting and ordinary Kriging interpolation method.We prosposed the Fast DTW matching criterion combined with sliding window optimization algorithm to reduce time consuming proposed,the positioning.increased computational efficiency by 40.(3)We analyze the characteristics of pedestrian behavior,and use the improved SVD-DT algorithm achieving pedestrian movement mode,the accuracy is 86.3%.Facing the problem of gait detection and step estimation mistakes caused by the unstable speeds,we proposed the peak detection algorithm based on adaptive threshold update,and imoproved Kim-step model.We use the quaternion and unscented Kalman filter heading algorithm,the experimental results show that the algorithm is significantly improved.(4)We use the smartphone test the magnetic positioning and the improved PDR algorithm in the real indoor scene.We proposed the geomagnetic/PDR fusion localization algorithm based on particle filter,the resultpositioning accuracy is increased by at least 0.3m under the indoor environment.