Instantaneous Best Integer Equivariant Position Estimation Using Google Pixel 4 Smartphones for Single- and Dual-Frequency, Multi-GNSS Short-Baseline RTK.

best integer equivariant (BIE) mean squared error (MSE) multi-GNSS real-time kinematic (RTK) smartphone positioning

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
16 May 2022
Historique:
received: 10 02 2022
revised: 09 05 2022
accepted: 09 05 2022
entrez: 28 5 2022
pubmed: 29 5 2022
medline: 29 5 2022
Statut: epublish

Résumé

High-precision global navigation satellite system (GNSS) positioning and navigation can be achieved with carrier-phase ambiguity resolution when the integer least squares (ILS) success rate (SR) is high. The users typically prefer the float solution under the scenario of having a low SR, and the ILS solution when the SR is high. The best integer equivariant (BIE) estimator is an alternative solution since it minimizes the mean squared errors (MSEs); hence, it will always be superior to both its float and ILS counterparts. There has been a recent development of GNSSs consisting of the Global Positioning System (GPS), Galileo, Quasi-Zenith Satellite System (QZSS), and the BeiDou Navigation Satellite System (BDS), which has made precise positioning with Android smartphones possible. Since smartphone tracking of GNSS signals is generally of poorer quality than with geodetic grade receivers and antennas, the ILS SR is typically less than one, resulting in the BIE estimator being the preferred carrier phase ambiguity resolution option. Therefore, in this contribution, we compare, for the first time, the BIE estimator to the ILS and float contenders while using GNSS data collected by Google Pixel 4 (GP4) smartphones for short-baseline real-time kinematic (RTK) positioning. It is demonstrated that the BIE estimator will always give a better RTK positioning performance than that of the ILS and float solutions while using both single- and dual-frequency smartphone GNSS observations. Lastly, with the same smartphone data, we show that BIE will always be superior to the float and ILS solutions in terms of the MSEs, regardless of whether the SR is at high, medium, or low levels.

Identifiants

pubmed: 35632180
pii: s22103772
doi: 10.3390/s22103772
pmc: PMC9143958
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Geoscience Australia
ID : 1002B

Références

Sensors (Basel). 2021 Dec 13;21(24):
pubmed: 34960412
Sensors (Basel). 2022 Feb 08;22(3):
pubmed: 35162034

Auteurs

Chien Zheng Yong (CZ)

National School of Surveying, University of Otago, 310 Castle Street, Dunedin 9016, New Zealand.
Geomatic Innovation Research Group, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia.

Ken Harima (K)

Geoscience Australia, GPO Box 378, Canberra, ACT 2601, Australia.

Eldar Rubinov (E)

FrontierSI, Goods Shed, Village Street, Docklands, VIC 3008, Australia.

Simon McClusky (S)

Geoscience Australia, GPO Box 378, Canberra, ACT 2601, Australia.
Research School of Earth Sciences, Australian National University, Canberra, ACT 2601, Australia.

Robert Odolinski (R)

National School of Surveying, University of Otago, 310 Castle Street, Dunedin 9016, New Zealand.

Classifications MeSH