Abstract
Abstract In this article, we investigate experimentally the suitability of several Bayesian filtering techniques for the problem of tracking a moving device by a set of wireless sensor nodes in indoor environments. In particular, we consider a setup where a robot was equipped with an ultra-wideband (UWB) node emitting ranging signals; this information was captured by a network of static UWB sensor nodes that were in charge of range computation. With the latter, we ran, analyzed, and compared filtering techniques to track the robot. Namely, we considered methods falling into two families: Gaussian filters and particle filters. Results shown in the article are with real data and correspond to an experimental setup where the wireless sensor network was deployed. Additionally, statistical analysis of the real data is provided, reinforcing the idea that in this kind of ranging measurements, the Gaussian noise assumption does not hold. The article also highlights the robustness of a particular filter, namely the cost-reference particle filter, to model inaccuracies which are typical in any practical filtering algorithm.
Highlights
Wireless sensor networks (WSNs) enable a plethora of applications, from which localization of moving devices appears as an appealing feature that complements global navigation satellite systems (GNSSs) based localization, especially in places where GNSS signals are very weak, such as in indoor environments, or in situations where the portion of in-view sky is small, such as urban areas with tall buildings
From the wide range of wireless technologies available for WSNs, we focus our attention on impulse-radiobased ultra-wideband (UWB), a technology that has a number of inherent properties, which are well suited to sensor network applications
Recall that a robot was moved along a trajectory while emitting an UWB ranging signal; such signal was received by a set of UWB sensors located in an office environment with known locations
Summary
Wireless sensor networks (WSNs) enable a plethora of applications, from which localization of moving devices appears as an appealing feature that complements (or substitutes) global navigation satellite systems (GNSSs) based localization, especially in places where GNSS signals are very weak, such as in indoor environments, or in situations where the portion of in-view sky is small, such as urban areas with tall buildings.There is extensive literature available on the topic, see for instance [1,2] and references therein. Wireless sensor networks (WSNs) enable a plethora of applications, from which localization of moving devices appears as an appealing feature that complements (or substitutes) global navigation satellite systems (GNSSs) based localization, especially in places where GNSS signals are very weak, such as in indoor environments, or in situations where the portion of in-view sky is small, such as urban areas with tall buildings. From the wide range of wireless technologies available for WSNs, we focus our attention on impulse-radiobased ultra-wideband (UWB), a technology that has a number of inherent properties, which are well suited to sensor network applications. UWB technology has a very good time-domain resolution allowing for precise localization and tracking, and its noise-like signal properties create little interference to other systems and are resistant to severe multipath and jamming. In [10], authors provided an overview of the IEEE 802.15.4a standard, which adopts UWB impulse radio to ensure robust data communications and precision ranging
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