| Location based service is widely used in safety first-aid,warehouse logistics,personal navigation and many other fields.human activities arise in the indoor environment for more than 80% of the time.Therefore,indoor positioning applications for large shopping malls,airports,subways,underground and other places have been demanded in recent years.As it continues to climb,indoor positioning technology has become a research hotspot.Wi Fi has the characteristics of wide coverage and high terminal support,and smart phones are also integrated with various types of inertial sensors.So the fusion positioning technology based on WiFi and multi-sensor has become the mainstream technology of indoor positioning.Aiming at the fusion positioning methods based on currently highly practical WiFi positioning and inertial measurement positioning,this thesis is studied in the following three aspects:Firstly,aiming at the effect of indoor Wi Fi Gaussian noise and non-line of sight on signal strength,the received signal strength is pre-processed and used to establish an offline fingerprint database.WiFi online positioning uses improved WKNN algorithm for matching the positioning where the RSSI relative deviation of the positioning reference point and K nearest neighbor points is used as the weight correction for the Euclidean distance.The simulation results show that the improved WKNN algorithm has higher positioning accuracy and more stable location performance than KNN and WKNN algorithm.Secondly,according to the cumulative error of the pedestrian dead reckoning(Pedestrian Dead Reckoning,PDR)positioning,the gait is accurately detected by acceleration threshold + peak and valley + time method,and online steps estimation is used by the improved offline step method in addition to step-sliding window method.The experimental results show that the gait detection of the triple constraint is of high accuracy and versatility,and an improved step length method is used can dynamically and accurately estimate the pedestrian's step by obtaining the step size parameter online,using the mean filter suppress direction sensor's error to accurately determine the direction.Finally,aiming at the problem of low accuracy of indoor WiFi positioning and the accumulated error of Pedestrian Dead Reckoning positioning,an indoor WiFi and PDR fused positioning algorithm based on Extended Kalman Filtering(EKF)is proposed.The simulation results show that the performance of Extended Kalman based Wi Fi-PDR indoor fused positioning algorithm is significantly better than that of Wi Fi or PDR positioning,Furthermore,the positioning performance has good robustness in spite of multiple track turnings,which can achieve high accuracy and reliable positioning applications. |
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