Evidence map›Paper›PMID 41682573›Full record

ArticleSensors (Basel, Switzerland)2026

Three-Dimensional Mapping-Aided Global Navigation Satellite System in Global Navigation Satellite System-Accessible Indoor Areas.

Hoi-Wah Ng, Hoi-Fung Ng, Li-Ta Hsu, John-Ross Rizzo

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hoi-Wah NgDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong, China.ORCID 0009-0007-5799-8544
Hoi-Fung NgDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong, China.ORCID 0000-0001-8668-6290
Li-Ta HsuDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong, China.ORCID 0000-0002-0352-741X
John-Ross RizzoDepartment of Physical Medicine and Rehabilitation, New York University Langone Health, New York, NY 10016, USA.ORCID 0000-0002-4084-0085

Funding

Innovation and Technology Fund - Innovation and Technology Support Programme (ITF-ITSP) ITS/091/23National Eye Institute and Fogarty International Center R33EY033689National Science Foundation ITE-2345139
6 · The paper itself

Abstract

The Global Navigation Satellite System (GNSS) is commonly used for outdoor positioning. However, its effectiveness diminishes in urban canyons and indoor environments attributed to signal blockage. This study aims to explore the potential of GNSS signals penetrating indoor spaces through windows and to enhance indoor positioning with Three-Dimensional Mapping-Aided (3DMA) GNSS, a concept generally applied outdoors. The research employs a 3D model of a corridor with manually labeled window locations to predict satellite visibility within indoor areas. The study integrates Pedestrian Dead Reckoning (PDR) with an indoor Shadow-matching (I-SM) technique, utilizing an Extended Kalman Filter (EKF) to improve positioning accuracy. One of the findings indicates that the proposed method significantly enhances positioning performance and its availability, achieving a root mean square error (RMSE) that is 2 m better than using PDR alone or single epoch I-SM. The study concludes that integrating GNSS with I-SM technique and PDR can optimize an indoor positioning solution and highlights the potential for improved navigation solutions in complex urban environments.

Indexed as

3DMA GNSSBIMindoor positioningLiDARseamless positioning

Identifiers

PMID41682573
PMCPMC12899897

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.