Evidence map›Paper›PMID 35458967›Full record

ArticleSensors (Basel, Switzerland)2022

NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models.

Karin Mascher, Markus Watzko, Axel Koppert, Julian Eder, Peter Hofer, Manfred Wieser

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Advances in Indoor Positioning and Indoor Navigation.Sensors (Basel, Switzerland) · 2022
    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.

Karin MascherTU Graz, Working Group Navigation, Institute of Geodesy, 8010 Graz, Austria.ORCID 0000-0001-7576-9760
Markus WatzkoTU Graz, Working Group Navigation, Institute of Geodesy, 8010 Graz, Austria.
Axel KoppertOHB Digital Solutions GmbH, 8044 Graz, Austria.ORCID 0000-0002-8723-6352
Julian EderIL-Ingenieurbüro Laabmayr & Partner ZT GmbH, 5020 Salzburg, Austria.
Peter HoferTheresian Military Academy, Institute for Advanced Officer Training, 2700 Wiener Neustadt, Austria.
Manfred WieserTU Graz, Working Group Navigation, Institute of Geodesy, 8010 Graz, Austria.

Funding

Austrian Research Promotion Agency 879691
6 · The paper itself

Abstract

Blue force tracking represents an essential task in the field of military applications. A blue force tracking system provides the location information of their own forces on a map to commanders. For the command post, this results in more efficient operation control with increasing safety. In underground structures (e.g., tunnels or subways), the localisation is challenging due to the lack of GNSS signals. This paper presents a localisation system for military or emergency forces tailored to usage in complex underground structures. In a particle filter, position changes from a dual foot-mounted INS are fused with opportunistic UWB ranges and data from a 3D tunnel model to derive position information. A concept to deal with the absence of UWB infrastructure or 3D tunnel models is illustrated. Recurrent neural network methodologies are applied to cope with different motion types of the operators. The evaluation of the positioning algorithm took place in a street tunnel. If a fully installed infrastructure was available, positioning errors under one metre were reached. The results also showed that the INS can bridge UWB outages. A particle-filter-based approach to UWB anchor mapping is presented, and the first simulation results showed its viability.

Indexed as

AlgorithmsFootHumansMotionReflex, StartleSomatoform Disorders3D modelblue force trackingfoot-mounted inertial navigationindoor localisationmachine learningmulti-sensor fusiontunnel modelUWB

Identifiers

PMID35458967
PMCPMC9028065

What OpenQuestion holds

Textmetadata
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.