Performance Bounds for Multipath-Assisted Indoor Navigation and Tracking (MINT)
The MINT (Multipath-assisted Indoor Navigation and Tracking) problem exploits the geometry of deterministic Multi-Path Components (MPCs) for robust indoor positioning in Line-Of-Sight (LOS) and non-LOS situations. It assumes a known room layout and can thus easily make use of signals reflected by the walls, for instance. In this paper, the Cramer-Rao lower bound of the positioning error is derived for this problem. This requires a novel channel model, where diffuse multipath is modeled as a colored Gaussian process that influences the effective SNR of deterministic MPCs. The adverse effect of path overlap is demonstrated and discussed. Computational results show the three-fold importance of a large signal bandwidth.