Research On Localization Algorithm Based On WiFi Signal Strength And Pedestrian Dead Reckoning

In the indoor localization system,the location accuracy based on WiFi technology relies heavily on the signal stability,and the multipath effect and Non Line of Sight(NLOS)of the signal may cause the node data to be anomalous and increase the localization error.Pedestrian dead reckoning(PDR)localization system can generate cumulative errors due to the sensor parameter and noise.To address the above problems,three main research works are done in this paper as follows:1.An improved WiFi signal strength localization algorithm is proposed.Firstly,suitable reference nodes are selected based on the distance information,and the suitable nodes are combined to generate different subsets of nodes;then,by using least square method on the subset of nodes,the existence of anomalous nodes is judged;and finally,according to the node situation,the least square method and least absolute deviation are combined to obtain the estimated position of the unlocated node.After experiments and analysis,the improved algorithm has better performance than the traditional least square method and least absolute deviation.2.An improved PDR localization algorithm is proposed.The algorithm improves the fixed parameters in step estimation into variable parameters by fuzzy logic,and then performs corner position correction and periodic position correction for PDR based on WiFi localization results.The experimental results show that the improved PDR algorithm has higher positioning accuracy.3.A WiFi and PDR fusion localization algorithm based on Extend Kalman Filter(EKF)is proposed.The algorithm fuses the improved PDR and WiFi localization results by EKF to reduce the cumulative error of PDR localization and the random error of WiFi localization.The experimental results show that the fusion method improves the accuracy of indoor localization and can obtain better localization results.