Robust tracking in mixed LOS/NLOS environments

Non-line-of-sight (NLOS) error is one of the most important factors affecting the accuracy of positioning or tracking especially in urban or indoor environments. This paper concentrates on alleviating the influence of the NLOS error. A position detection approach utilizing the circle error probability (CEP) in conjunction with the least square (LS) method and Kaiman Filter (KF) tracking algorithms is proposed. The LS is used to estimate the positions of a moving target from time-of-arrival (TOA) measurements and the KF is used to smooth the tracking trajectory. Simulation results show that this approach can effectively identify line-of-sight (LOS) estimated positions, leading to higher tracking accuracy than that by other tracking methods without using position detection.