Evidence map›Paper›PMID 36904989›Full record

ArticleSensors (Basel, Switzerland)2023

RadarPDR: Radar-Assisted Indoor Pedestrian Dead Reckoning.

Jianbiao He, Wei Xiang, Qing Zhang, Bang Wang

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Article in Sensors (Basel, Switzerland), 2023. 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. 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

4 authors.

Jianbiao HeShenzhen Polytechnic (SZPT), Liuxian Avenue 7098, Shenzhen 518055, China.
Wei XiangSchool of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Luoyu Road 1037, Wuhan 430074, China.
Qing ZhangHubei International Trade Supply Chain Management Co., Ltd., Wuhan 430000, China.
Bang WangSchool of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Luoyu Road 1037, Wuhan 430074, China.ORCID 0000-0002-0312-4805

Funding

Shenzhen key technology research project: key technology research and development of high-speed and high-precision vertical five-axis machining center 2019N048
6 · The paper itself

Abstract

Pedestrian dead reckoning (PDR) is the critical component in indoor pedestrian tracking and navigation services. While most of the recent PDR solutions exploit in-built inertial sensors in smartphones for next step estimation, due to measurement errors and sensing drift, the accuracy of walking direction, step detection, and step length estimation cannot be guaranteed, leading to large accumulative tracking errors. In this paper, we propose a radar-assisted PDR scheme, called RadarPDR, which integrates a frequency-modulation continuous-wave (FMCW) radar to assist the inertial sensors-based PDR. We first establish a segmented wall distance calibration model to deal with the radar ranging noise caused by irregular indoor building layouts and fuse wall distance estimation with acceleration and azimuth signals measured by the inertial sensors of a smartphone. We also propose a hierarchical

Indexed as

indoor trackingpedestrian dead reckoningradar ranging and correctiontrajectory correction

Identifiers

PMID36904989
PMCPMC10007269

What OpenQuestion holds

Textfull text, public
LicenceCC BY
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table measurements read2
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.