Next Article in Journal
Rapid Detection of Windthrows Using Sentinel-1 C-Band SAR Data
Previous Article in Journal
A Patch-Based Light Convolutional Neural Network for Land-Cover Mapping Using Landsat-8 Images
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2019, 11(2), 116; https://doi.org/10.3390/rs11020116

A Unified Model for Multi-Frequency PPP Ambiguity Resolution and Test Results with Galileo and BeiDou Triple-Frequency Observations

1,2,* , 3,* , 4
and
1
1
Geodetic Institute, Karlsruhe Institute of Technology, D-76131 Karlsruhe, Germany
2
Zhengzhou Institute of Surveying and Mapping, Zhengzhou 450052, China
3
The German Research Centre for Geosciences (GFZ), D-14473 Potsdam, Germany
4
Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada
*
Authors to whom correspondence should be addressed.
Received: 11 December 2018 / Revised: 3 January 2019 / Accepted: 7 January 2019 / Published: 10 January 2019
Full-Text   |   PDF [4385 KB, uploaded 10 January 2019]   |  

Abstract

With the modernization of Global Navigation Satellite System (GNSS), triple- or multi-frequency signals have become available from more and more GNSS satellites. The additional signals are expected to enhance the performance of precise point positioning (PPP) with ambiguity resolution (AR). To deal with the additional signals, we propose a unified modeling strategy for multi-frequency PPP AR based on raw uncombined observations. Based on the unified model, the fractional cycle biases (FCBs) generated from multi-frequency observations can be flexibly used, such as for dual- or triple- frequency PPP AR. Its efficiency is verified with Galileo and BeiDou triple-frequency observations collected from globally distributed MGEX stations. The estimated FCB are assessed with respect to residual distributions and standard deviations. The obtained results indicate good consistency between the input float ambiguities and the generated FCBs. To assess the performance of the triple-frequency PPP AR, 11 days of MGEX data are processed in three-hour sessions. The positional biases in the ambiguity-fixed solutions are significantly reduced compared with the float solutions. The improvements are 49.2%, 38.3%, and 29.6%, respectively, in east/north/up components for positioning with BDS, while the corresponding improvements are 60.0%, 29.0%, and 21.1% for positioning with Galileo. These results confirm the efficiency of the proposed approach, and that the triple-frequency PPP AR can bring an obvious benefit to the ambiguity-float PPP solution. View Full-Text
Keywords: Galileo; BeiDou; precise point positioning; integer ambiguity resolution; triple-frequency; fractional cycle bias Galileo; BeiDou; precise point positioning; integer ambiguity resolution; triple-frequency; fractional cycle bias
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Xiao, G.; Li, P.; Gao, Y.; Heck, B. A Unified Model for Multi-Frequency PPP Ambiguity Resolution and Test Results with Galileo and BeiDou Triple-Frequency Observations. Remote Sens. 2019, 11, 116.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top