Abstract

We address the indoor tracking problem by combining an Impulse Radio-Ultra-Wideband handset with an ankle-mounted Inertial Measurement Unit embedding an accelerometer and a gyroscope. The latter unit makes possible the detection of the stance phases to overcome velocity drifts. Regarding radiolocation, a time-of-arrival estimator adapted to energy-based receivers is applied to mitigate the effects of dense multipath profiles. A novel quality factor associated with this estimator is also provided as a function of the received signal-to-noise ratio, enabling us to identify outliers corresponding to obstructed radio links and to scale the covariance matrix of radiolocation measurements. Finally, both radio and inertial subsystems are loosely-coupled into one single navigation solution relying on a specific extended Kalman filter. In the proposed fusion strategy, processed inertial data control the filter state prediction whereas Combined Time Differences Of Arrival are formed as input observations. These combinations offer low computational complexity as well as a unique filter structure over time, even after removing outliers. Experimental results obtained in a representatively harsh indoor environment emphasize the complementarity of the two technologies and the relevance of the chosen fusion method while operating with low-cost, noncollocated, asynchronous, and heterogeneous sensors.

Highlights

  • For the last past years, new location and tracking (LT) needs have been gradually introduced into a wide variety of applications, such as security, health care, rescue, logistics; or house automation

  • This is due to the combined harmful effects of generalized NLOS links, to body shadowing, and to poor geometric dilution of precision (GDOP) conditions

  • As expected, fusing the two subsystems reduces systematically the overall error, even if the enhancement is far more spectacular in Room B in comparison with both scenarios 3 and 4. These results open the floor to parsimonious fusion schemes, where one could switch from a stand-alone subsystem into the complete fusion-oriented system on demand, depending on the operating conditions, saving energy and complexity at the price of slight performance degradations

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Summary

Introduction

For the last past years, new location and tracking (LT) needs have been gradually introduced into a wide variety of applications, such as security, health care, rescue, logistics; or house automation. A growing interest has been more expressed in location-dependent indoor services, which require seamless pedestrian navigation capabilities in harsh environments where satellite-based solutions cannot operate. In this context, alternative technologies are currently under investigation, based on for example, location-enabled wireless networks [1, 2]. Alternative technologies are currently under investigation, based on for example, location-enabled wireless networks [1, 2] On their own, most of modern wireless networks can retrieve the positions of mobile radio devices relative to the known position of reference anchors or base stations (BS). Several TOA-based range measurements collected (with respect to fixed BSs with known locations) can feed positioning or tracking algorithms to solve out a circular (resp., spherical) location estimation problem in 2D (resp., 3D)

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