Abstract
Mixed sigh conditions include line-of-sight/non-line-of-sight (LOS/ NLOS) conditions, which have adverse impact on the precision for mobility positioning. A first-order Markov model is employed to describe the dynamic transition of sight conditions, which is hidden in measured data. A Rao-Blackwellized Particle filter (RBPF) is proposed to jointly estimate mobile state and the hidden sight state based on the measurement. Simulation results show the effectiveness of the method.
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