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Recent Advances in GNSS-Based High Precision Positioning Technology: Part II

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Dear Colleagues,

Global navigation satellite systems (GNSSs) are the technology of choice for most position-related applications when available. The main challenges of GNSS technology arise when operating in complex environments that are either naturally impaired (i.e., by multipath, shadowing, high dynamics, or ionospheric scintillation) or subject to intentional or unintentional interference. Ushered in by an increasing demand for availability, accuracy, and reliability, the mitigation of these challenges has steered intense research on advanced receiver design. These requirements are imposed by critical applications such as autonomous driving, power grids, classical aviation, terrestrial navigation, and unmanned aerial and ground vehicles.

Unprecedented improvements in position, navigation, and timing (PNT) technologies based on GNSS are currently being developed, regardless of the known limitations of GNSS in terms of anywhere/anytime availability. Those solutions encompass snapshot-based receivers, high sensitivity, and high-precision techniques that are shaping the future of GNSS receivers through advanced signal processing and machine learning tools.

The aim of this Special Issue is to collect high-quality research articles and review papers on advances in high-precision GNSS receiver design. Methodological papers are welcome, although articles including experimental results are highly appreciated. Original, high-quality contributions that have not been published before and are not currently under review by other journals or conferences are sought.

This Special Issue invites contributions in the following topics (but is not limited to them):

Advances in precise point positioning (PPP);
Advances in real-time kinematic (RTK) positioning;
Baseband signal processing for high-precision GNSS receivers;
Performance bounds in high-precision navigation;
High-sensitivity receivers;
Precise position, navigation, and timing (PNT) in challenging environments;
Countermeasures to harsh propagation conditions;
Cooperative precise PNT;
Cloud-based solutions for precise PNT;
Adaptive and robust techniques enabling high-precision navigation.

Prof. Dr. Jordi Vilà-Valls

Prof. Dr. Wenyi Wang
Prof. Dr. Pau Closas
Guest Editors

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Keywords

Global navigation satellite systems
Precise point positioning
Real-time kinematics
High-precision positioning
High-sensitivity receivers
Cloud-based navigation
Performance bounds
Cooperative navigation
Robust navigation

Published Papers (1 paper)

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21 pages, 5332 KiB

Open AccessArticle

An Improved Long-Period Precise Time-Relative Positioning Method Based on RTS Data

by Yangwei Lu, Shengyue Ji, Rui Tu, Duojie Weng, Xiaochun Lu and Wu Chen

Sensors 2021, 21(1), 53; https://doi.org/10.3390/s21010053 - 24 Dec 2020

Cited by 1 | Viewed by 2167

Abstract

The high precision positioning can be easily achieved by using real-time kinematic (RTK) and precise point positioning (PPP) or their augmented techniques, such as network RTK (NRTK) and PPP-RTK, even if they also have their own shortfalls. A reference station and datalink are required for RTK or NRTK. Though the PPP technique can provide high accuracy position data, it needs an initialisation time of 10–30 min. The time-relative positioning method estimates the difference between positions at two epochs by means of a single receiver, which can overcome these issues within short period to some degree. The positioning error significantly increases for long-period precise positioning as consequence of the variation of various errors in GNSS (Global Navigation Satellite System) measurements over time. Furthermore, the accuracy of traditional time-relative positioning is very sensitive to the initial positioning error. In order to overcome these issues, an improved time-relative positioning algorithm is proposed in this paper. The improved time-relative positioning method employs PPP model to estimate the parameters of current epoch including position vector, float ionosphere-free (IF) ambiguities, so that these estimated float IF ambiguities are used as a constraint of the base epoch. Thus, the position of the base epoch can be estimated by means of a robust Kalman filter, so that the position of the current epoch with reference to the base epoch can be obtained by differencing the position vectors between the base epoch and the current one. The numerical results obtained during static and dynamic tests show that the proposed positioning algorithm can achieve a positioning accuracy of a few centimetres in one hour. As expected, the positioning accuracy is highly improved by combining GPS, BeiDou and Galileo as a consequence of a higher amount of used satellites and a more uniform geometrical distribution of the satellites themselves. Furthermore, the positioning accuracy achieved by using the positioning algorithm here described is not affected by the initial positioning error, because there is no approximation similar to that of the traditional time-relative positioning. The improved time-relative positioning method can be used to provide long-period high precision positioning by using a single dual-frequency (L1/L2) satellite receiver. Full article

(This article belongs to the Special Issue Recent Advances in GNSS-Based High Precision Positioning Technology: Part II)

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Recent Advances in GNSS-Based High Precision Positioning Technology: Part II

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