Multiple-Model Mobile Localization Based on Unscented Kalman Filter in Mixed Indoor

Abstract

In this paper, we present an Interactive multiple mode-Unscented Kalman filter (IMM-UKF) algorithm to achieve mobile node location under wireless sensor networks environments. In the IMM structure, UKF and Variational Bayesian Adaptive Method based on UKF are adapted in parallel, which can improve positioning accuracy in the process of line-of sight (LOS) and non-line-of-sight (NLOS) signal state switching. The estimated values by filtering are fused according to the weighting factors to get the estimated positions. Moreover, when NLOS measurement noise covariance change, we propose Variational Bayesian Adaptive Method based on UKF to improve robustness. Both Simulation and experiments illustrate that the propose algorithm performs can achieve competitive localization accuracy.