Parallel Kalman Filtering Based NLOS Localization in Wireless Sensor Network

This paper solves the problem of localization of mobile node in mixed line-of-sight/non-line-of-sight (LOS/NLOS) environments. To improve the localization accuracy, a parallel Kalman filtering algorithm is proposed to locate the robot mobile node. This algorithm consists of two steps: We firstly calculate the LOS/NLOS mode probabilities, then the proposed algorithm combines the estimation results of the two parallel Kalman filters according to the mode probabilities. It is shown that this algorithm can efficiently mitigate the NLOS effect of the measurement range error. Simulation results show that the proposed algorithm significantly improves the accuracy of localization in mixed LOS/NLOS environments.