Wireless indoor positioning based on filtering algorithm

The paper proposed filtering algorithms for wireless indoor localization based on Extended Kalman filtering (EKF) and Uncented Kalman filtering (UKF). When we use EKF linearization to deal with nonlinear problems, it may cause precision decrease and a series of problems. Thus, the rigorous mathematical analysis simulations and comparative results were carried out in this paper to compare EKF and UKF for the wireless indoor localization. Finally, the advantages and disadvantages of two algorithms and their respective applications were obtained. The simulation results show that the algorithm accuracy of UKF is higher than that of EKF, especially in the nonlinear environment.