Multipath-assisted maximum-likelihood indoor positioning using UWB signals

Multipath-assisted indoor positioning (using ultrawideband signals) exploits the geometric information contained in deterministic multipath components. With the help of a-priori available floorplan information, robust localization can be achieved, even in absence of a line-of-sight connection between anchor and agent. In a recent work, the Cramér-Rao lower bound has been derived for the position estimation variance using a channel model which explicitly takes into account diffuse multipath as a stochastic noise process in addition to the deterministic multipath components. In this paper, we adapt this model for position estimation via a measurement likelihood function and evaluate the performance for real channel measurements. Performance results confirm the applicability of this approach. A position accuracy better than 2.5 cm has been obtained in 90% of the estimates using only one active anchor at a bandwidth of 2GHz and robustness against non-line-of-sight situations has been demonstrated.