Auto-regressive modeling of shadowing for RSS mobile tracking
نویسنده
چکیده
In this paper, we consider the tracking of mobile terminals based on the received signal strength (RSS) measured from several base stations. The spatial correlation of the random shadowing is exploited in order to improve the position tracking. We define an auto-regressive (AR) model of the temporal evolution of the shadowing. This model allows for performing a joint tracking of the position and the shadowing by applying a RaoBlackwellized (RB) particle filter approximating the posterior probability distributions numerically. The simulation results show that the tracking can be improved by considering sufficiently high auto-regressive orders.
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