Multipath-based Localization and Tracking considering Off-Body Channel Effects
In this work we consider multipath-based positioning and tracking in off-body channels. We analyse the effects introduced by the human body and the resulting effects that are of interest in positioning and tracking based on channel measurements obtained in an indoor scenario. As the signal bandwidth is known to effect the achievable accuracy in positioning, the bandwidth dependency of the field of view (FOV) induced by human body via shadowing and the number of multipath components (MPCs) detected and estimated by a deterministic maximum likelihood (ML) algorithm is investigated. A multipath-based positioning and tracking algorithm is proposed that associates estimated MPC parameters with floor plan features and exploits a human body-dependent FOV function. The proposed algorithm is able to provide accurate position estimates even for an off-body radio channel in a multipath-prone environment with the signal bandwidth found to be a limiting factor.
The figure shows the CDFs for the position error along a track consisting of 900 measured channel responses between a mobile device and two anchors. The mobile device was attached to the upper torso of a user moving through an indoor environment. The best performance is achieved when using a FOV function for selecting visible anchors (virtual and physical) for the data association stage in combination with a large signal bandwidth (2 or 4 GHz).
This paper was submitted to the EuCAP-2022 with a pre-print available on Arxiv
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