  We present a message passing algorithm for localization and tracking in
multipath-prone environments that implicitly considers obstructed line-of-sight
situations. The proposed adaptive probabilistic data association algorithm
infers the position of a mobile agent using multiple anchors by utilizing delay
and amplitude of the multipath components (MPCs) as well as their respective
uncertainties. By employing a nonuniform clutter model, we enable the algorithm
to facilitate the position information contained in the MPCs to support the
estimation of the agent position without exact knowledge about the environment
geometry. Our algorithm adapts in an online manner to both, the time-varying
signal-to-noise-ratio and line-of-sight (LOS) existence probability of each
anchor. In a numerical analysis we show that the algorithm is able to operate
reliably in environments characterized by strong multipath propagation, even if
a temporary obstruction of all anchors occurs simultaneously.
