Evidence map›Paper›PMID 38794057›Full record

ArticleSensors (Basel, Switzerland)2024

Location-Aware Range-Error Correction for Improved UWB Localization.

Sander Coene, Chenglong Li, Sebastian Kram, Emmeric Tanghe, Wout Joseph, David Plets

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Sander CoeneWAVES Group, Department of Information Technology, Ghent University-imec, 9052 Ghent, Belgium.ORCID 0000-0002-0425-2841
Chenglong LiCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.ORCID 0000-0003-3261-5619
Sebastian KramInformation Technology (Communication Electronics), University Erlangen-Nuernberg, 91058 Erlangen, Germany.ORCID 0000-0002-4907-791X
Emmeric TangheWAVES Group, Department of Information Technology, Ghent University-imec, 9052 Ghent, Belgium.ORCID 0000-0003-0020-6466
Wout JosephWAVES Group, Department of Information Technology, Ghent University-imec, 9052 Ghent, Belgium.ORCID 0000-0002-8807-0673
David PletsWAVES Group, Department of Information Technology, Ghent University-imec, 9052 Ghent, Belgium.ORCID 0000-0002-8879-5076

Funding

Excellence of Science (EOS) MUlti-SErvice WIreless NETworks (MUSE-WINET)IMEC project AAA UWB-IRResearch Foundation - Flanders G098020N
6 · The paper itself

Abstract

In this paper, we present a novel localization scheme, location-aware ranging correction (LARC), to correct ranging estimates from ultra wideband (UWB) signals. Existing solutions to calculate ranging corrections rely solely on channel information features (e.g., signal energy, maximum amplitude, estimated range). We propose to incorporate a preliminary location estimate into a localization chain, such that location-based features can be calculated as inputs to a range-error prediction model. This way, we can add information to range-only measurements without relying on additional hardware such as an inertial measurement unit (IMU). This improves performance and reduces overfitting behavior. We demonstrate our LARC method using an open-access measurement dataset with distances up to 20 m, using a simple regression model that can run purely on the CPU in real-time. The inclusion of the proposed features for range-error mitigation decreases the ranging error 90th percentile (P90) by 58% to 15 cm (compared to the uncorrected range error), for an unseen trajectory. The 2D localization P90 error is improved by 21% to 18 cm. We show the robustness of our approach by comparing results to a changed environment, where metallic objects have been moved around the room. In this modified environment, we obtain a 56% better P90 ranging performance of 16 cm. The 2D localization P90 error improves as much as for the unchanged environment, by 17% to 18 cm, showing the robustness of our method. This method evolved from the first-ranking solution of the 2021 and 2022 International Conference on Indoor Position and Indoor Navigation (IPIN) Competition.

Indexed as

localizationsignal processing algorithmstime of arrival estimationultra wideband technology

Identifiers

PMID38794057
PMCPMC11125432

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.