Multipath-based Localization and Tracking considering Off-Body Channel Effects

TL;DR

This paper investigates multipath-based localization considering off-body effects, analyzing human body influence on signal properties, and proposes an algorithm that improves positioning accuracy in multipath-rich indoor environments.

Contribution

It introduces a novel multipath-based positioning and tracking algorithm that accounts for human body effects and signal bandwidth limitations.

Findings

Human body significantly affects multipath components and FOV in off-body channels.

Signal bandwidth influences the number of detectable multipath components.

The proposed algorithm achieves accurate positioning despite multipath and body effects.

Abstract

This paper deals with multipath-based positioning and tracking in off-body channels. An analysis of the effects introduced by the human body and the implications on positioning and tracking is presented based on channel measurements obtained in an indoor scenario. It shows the influence of the radio signal bandwidth on the human body induced field of view (FOV) and the number of multipath components (MPCs) detected and estimated by a deterministic maximum likelihood (ML) algorithm. A multipath-based positioning and tracking algorithm is proposed that associates these 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.