Mobile location estimation in urban areas using fuzzy-tuned IMM algorithm

In this paper, we present a plausible time-of-arrival (TOA)-based localization algorithm for mobile location estimation in urban areas. To achieve this goal, we propose a fuzzy-tuned system framework and a fuzzy-tuned interacting multiple-model (fuzzy-tuned IMM) algorithm. To mitigate the effects of both non-line-of-sight (NLOS) errors and mobility variations of a mobile station, the proposed algorithm identifies the LOS/NLOS conditions and then uses the result for fuzzy adaption of process noise covariances. This makes the proposed approach distinct from other existing methods. The proposed algorithm can perform more accurate and robust mobile positioning. Simulation results confirm the performance advantages of the proposed algorithm.