Description:

Our lab works on indoor localization methods that explicitly uses multipath components (MPCs), resulting from signal reflections at e.g. room walls [1]. One of the most challenging aspects in this scope is the actual extraction of the individual path parameters from actual measurements (channel impulse responses). At ultra-wide bandwidths, a wealth of MPCs are resolvable, while only a few of them correspond to the reflections that are useable. Most MPCs are caused by diffuse scattering processes and are more random in nature, resulting in ambiguities in the subsequent localization algorithms.

Recent analyses of our measurements [2], [3] however show that the usable reflections, coming from the room walls, are indeed detectable as correlated paths in the time-variant impulse response of the channel. This aim of this thesis is the tracking of these paths over a certain motion trajectory, making use of these correlations. As the number of expected reflected paths rapidly changes over such a movement path, multitarget tracking algorithms are used. It turns out that PHD filters are a promising approach to this problem [4]. Some variants of these filters should be implemented and tested both with simulated and with measured data.

Tasks:

• Literature survey with respect to multitarget tracking, especially PHD filters
• Implementation of some PHD filter variants in Matlab
• Performance evaluation using suitable metrics

Full Text

The full text of this thesis can be found here.

References:

[1] Meissner, P.; Gigl, T. and Witrisal, K.: _UWB Sequential Monte Carlo Positioning using Virtual Anchors,_International Conference on Indoor Positioning and Indoor Navigation, Zurich, 2010

[2] Fröhle, M.; Meissner, P.; Gigl, T. and Witrisal, K.: Scatterer and Virtual Source Detection for Indoor UWB Channels IEEE International Conference on Ultra-Wideband, 2011

[3] Meissner, P.; Arnitz, D.; Gigl, T. and Witrisal, K.: Analysis of an Indoor UWB Channel for Multipath-Aided Localization, IEEE International Conference on Ultra-Wideband, 2011

[4] Mahler, R. P. S.: Statistical Multisource-Multitarget Information Fusion, Artech House, 2007