Measurement and analysis of UWB radio channel for indoor localization in a hospital environment

Romme, Jac; Heuvel, J. H. C. van den; Dolmans, Guido; Selimis, Georgios; Philips, Kathleen; Groot, Harmke de

doi:10.1109/icuwb.2014.6958992

Cited by 8 publications

(12 citation statements)

References 13 publications

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“…Finally, we illustrate the performance of 2-D positioning based on estimated ranges between a mobile node and anchors. We use two indoor CFR datasets collected using a vector network analyzer (VNA) in a hospital [52], and a university building environment [53]. The single snapshots of CFR measurement are collected between multiple anchors and a mobile node moving on predefined trajectories in two different indoor environments.…”

Section: Real Data Experimentsmentioning

confidence: 99%

Delay Estimation for Ranging and Localization Using Multiband Channel State Information

Kazaz

Janssen

Romme

et al. 2022

IEEE Trans. Wireless Commun.

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In wireless networks, an essential step for precise range-based localization is the high-resolution estimation of multipath channel delays. The resolution of traditional delay estimation algorithms is inversely proportional to the bandwidth of the training signals used for channel probing. Considering that typical training signals have limited bandwidth, delay estimation using these algorithms often leads to poor localization performance. To mitigate these constraints, we exploit the multiband and carrier frequency switching capabilities of wireless transceivers and propose to acquire channel state information (CSI) in multiple bands spread over a large frequency aperture. The data model of the acquired measurements has a multiple shift-invariance structure, and we use this property to develop a high-resolution delay estimation algorithm. We derive the Cramér-Rao Bound (CRB) for the data model and perform numerical simulations of the algorithm using system parameters of the emerging IEEE 802.11be standard. Simulations show that the algorithm is asymptotically efficient and converges to the CRB. To validate modeling assumptions, we test the algorithm using channel measurements acquired in real indoor scenarios. From these results, it is seen that delays (ranges) estimated from multiband CSI with a total bandwidth of 320 MHz show an average RMSE of less than 0.3 ns (10 cm) in 90% of the cases.

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Section: Real Data Experimentsmentioning

confidence: 99%

Delay Estimation for Ranging and Localization Using Multiband Channel State Information

Kazaz

Janssen

Romme

et al. 2022

IEEE Trans. Wireless Commun.

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show abstract

“…This information is then integrated across each step to obtain a complete trajectory. The next position of the pedestrian could then be estimated with (1). The current position after the k th step (x k , y k ) is input into the equation.…”

Section: Pdrmentioning

confidence: 99%

“…The field is still developing at an incredible pace, with new insights continuously being reported. These Location-Based Services (LBS) are able to provide accurate location tracking of people, and they have started to be adopted in a range of different applications, such as smart environments, healthcare [1], pedestrian navigation, and emergency services [2]. It has also facilitated new ways of human-environment interaction, in which positional information could be leveraged to create responsive systems.…”

Section: Introductionmentioning

confidence: 99%

HeadSLAM: Pedestrian SLAM with Head-Mounted Sensors

Hou

Bergmann

2022

Sensors

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Research focused on human position tracking with wearable sensors has been developing rapidly in recent years, and it has shown great potential for application within healthcare, smart homes, sports, and emergency services. Pedestrian Dead Reckoning (PDR) with Inertial Measurement Units (IMUs) is one of the most promising solutions within this domain, as it does not rely on any additional infrastructure, whilst also being suitable for use in a diverse set of scenarios. However, PDR is only accurate for a limited period of time before unbounded errors, due to drift, affect the position estimate. Error correction can be difficult as there is often a lack of efficient methods for calibration. HeadSLAM, a method specifically designed for head-mounted IMUs, is proposed to improve the accuracy during longer tracking times (10 min). Research participants (n = 7) were asked to walk in both indoor and outdoor environments wearing head-mounted sensors, and the obtained HeadSLAM accuracy was subsequently compared to that of the PDR method. A significant difference (p < 0.001) in the average root-mean-squared error and absolute error was found between the two methods. HeadSLAM had a consist lower error across all scenarios and subjects in a 20 h walking dataset. The findings of this study show how the HeadSLAM algorithm can provide a more accurate long-term location service for head-mounted, low-cost sensors. The improved performance can support inexpensive applications for infrastructureless navigation.

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“…We use two indoor CFR datasets collected using a vector network analyzer (VNA) in a hospital [57], and a university building environment [58]. The single snapshots of CFR When collected with off-the-shelf transceivers, the CSI measurements might get affected by various hardware impairments.…”

Section: Real Data Experimentsmentioning

confidence: 99%

“…15. The CFR is measured over a set of 4096 equispaced frequency points starting from 5 to 10 GHz with a link budget of 110 dB [57]. This is equivalent to a subcarrier spacing of 1.22 MHz, which is 15.6 times higher than the IEEE 802.11be configuration.…”

Section: B Performance Of Positioningmentioning

confidence: 99%

Delay Estimation for Ranging and Localization Using Multiband Channel State Information

Kazaz,

Janssen,

Romme

et al. 2021

Preprint

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In wireless networks, an essential step for precise range-based localization is the high-resolution estimation of multipath channel delays. The resolution of traditional delay estimation algorithms is inversely proportional to the bandwidth of the training signals used for channel probing. Considering that typical training signals have limited bandwidth, delay estimation using these algorithms often leads to poor localization performance. To mitigate these constraints, we exploit the multiband and carrier frequency switching capabilities of wireless transceivers and propose to acquire channel state information (CSI) in multiple bands spread over a large frequency aperture. The data model of the acquired measurements has a multiple shift-invariance structure, and we use this property to develop a high-resolution delay estimation algorithm. We derive the Cramér-Rao Bound (CRB) for the data model and perform numerical simulations of the algorithm using system parameters of the emerging IEEE 802.11be standard. Simulations show that the algorithm is asymptotically efficient and converges to the CRB. To validate modeling assumptions, we test the algorithm using channel measurements acquired in real indoor scenarios. From these results, it is seen that delays (ranges) estimated from a multiband CSI with a total bandwidth of 320 MHz show an average RMSE of less than 0.3 ns (10 cm) in 90% of the cases.

show abstract

Measurement and analysis of UWB radio channel for indoor localization in a hospital environment

Cited by 8 publications

References 13 publications

Delay Estimation for Ranging and Localization Using Multiband Channel State Information

Delay Estimation for Ranging and Localization Using Multiband Channel State Information

HeadSLAM: Pedestrian SLAM with Head-Mounted Sensors

Delay Estimation for Ranging and Localization Using Multiband Channel State Information

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