Evidence map›Paper›PMID 32660069›Full record

ArticleSensors (Basel, Switzerland)2020

Unbalanced Hybrid AOA/RSSI Localization for Simplified Wireless Sensor Networks.

Anh Tuyen Le, Le Chung Tran, Xiaojing Huang, Christian Ritz, Eryk Dutkiewicz, Son Lam Phung, Abdesselam Bouzerdoum, Daniel Franklin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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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

8 authors.

Anh Tuyen LeSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong 2522, Australia.ORCID 0000-0002-9229-4557
Le Chung TranSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong 2522, Australia.ORCID 0000-0002-2677-8721
Xiaojing HuangSchool of Electrical and Data Engineering, University of Technology Sydney, Ultimo 2007, Australia.
Christian RitzSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong 2522, Australia.
Eryk DutkiewiczSchool of Electrical and Data Engineering, University of Technology Sydney, Ultimo 2007, Australia.
Son Lam PhungSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong 2522, Australia.ORCID 0000-0002-3076-0540
Abdesselam BouzerdoumSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong 2522, Australia.
Daniel FranklinSchool of Electrical and Data Engineering, University of Technology Sydney, Ultimo 2007, Australia.ORCID 0000-0002-9563-5943

Funding

Defence Innovation Network 2019- 888-006-985
6 · The paper itself

Abstract

Source positioning using hybrid angle-of-arrival (AOA) estimation and received signal strength indicator (RSSI) is attractive because no synchronization is required among unknown nodes and anchors. Conventionally, hybrid AOA/RSSI localization combines the same number of these measurements to estimate the agents' locations. However, since AOA estimation requires anchors to be equipped with large antenna arrays and complicated signal processing, this conventional combination makes the wireless sensor network (WSN) complicated. This paper proposes an unbalanced integration of the two measurements, called 1AOA/nRSSI, to simplify the WSN. Instead of using many anchors with large antenna arrays, the proposed method only requires one master anchor to provide one AOA estimation, while other anchors are simple single-antenna transceivers. By simply transforming the 1AOA/1RSSI information into two corresponding virtual anchors, the problem of integrating one AOA and

Indexed as

angle of arrival (AOA)positioningreceived signal strength indicator (RSSI)target localizationwireless sensor network (WSN)

Identifiers

PMID32660069
PMCPMC7411761

What OpenQuestion holds

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LicenceCC BY
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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.