Multipath-Assisted Maximum-Likelihood Indoor Positioning using UWB Signals

Result of the Month

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Multipath-assisted indoor positioning (using ultra-wideband 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 Cramer-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 work, we adapt this model for position estimation via a measurement likelihood function and evaluate the performance for real channel measurements. To find the global maximum of the highly multi-modal LHF, we introduced a particle filter method with swarm behavior optimization (PF-PSO). Performance results confirm the applicability of this approach and show the importance of considering diffuse multipath.

Contact: Erik Leitinger

Evaluations, using real measurement data, have shown that the orientation and size of the CRLB error ellipses fit well with the estimated co-variance ellipses of the estimator. Small deviations can be explained by the fact that the co-variance has to be estimated from a set of measurements rather than from a single measurement. The same holds for the estimation of parameters needed for the computation of the CRLB.  In a line-of-sight scenario considering diffuse multipath we achieved a position error of less than 2.5cm in 90% of the estimates for only one active anchor (see Figure 4 in paper).

For more information, take a look at our paper!

1. May 2014 - 31. May 2014