Positioning Optimization Technique in Non-Line-of-Sight Environment

A positioning optimization technique for non-lineof-sight environment is presented based on weighted orthogonal polynomial fitting technique and singular value decomposition. First, non-line-of-sight errors in TOA measurements are mitigated using weighted orthogonal polynomial fitting technique and the true range between the measuring terminal and the mobile station is approximated. Then the standard deviation of error in line-of-sight environment is exploited to give an optimal location estimation of the mobile station. Short-range measurements from movable measuring terminals are also included to overcome the performance limitation imposed by the measuring terminal bottleneck and translate the spatial reused benefits into positioning accuracy enhancement. Simulation and comparison results show that the proposed algorithm can get better performance measure and achieve high level of positioning accuracy in severe NLOS environment.