Investigation of Tightly Combined Single-Frequency and Single-Epoch Precise Positioning Using Multi-GNSS Data

Chenlong Deng,Jianhui Cui,Chi Guo,Qian Liu,Weiming Tang,Yawei Wang,Xuan Zou

doi:10.3390/rs12020285

Abstract

The loose combination (LC) and the tight combination (TC) are two different models in the combined processing of four global navigation satellite systems (GNSSs). The former is easy to implement but may be unusable with few satellites, while the latter should cope with the inter-system bias (ISB) and is applicable for few tracked satellites. Furthermore, in both models, the inter-frequency bias (IFB) in the GLObal NAvigation Satellite System (GLONASS) system should also be removed. In this study, we aimed to investigate the performance difference of ambiguity resolution and position estimation between these two models simultaneously using the single-frequency data of all four systems (GPS + GLONASS + Galileo + BeiDou Navigation Satellite System (BDS)) in three different environments, i.e., in an open area, with surrounding high buildings, and under a block of high buildings. For this purpose, we first provide the definition of ISB and IFB from the perspective of the hardware delays, and then propose practical algorithms to estimate the IFB rate and ISB. Thereafter, a comprehensive performance comparison was made between the TC and LC models. Experiments were conducted to simulate the above three observation environments: the typical situation and situations suffering from signal obstruction with high elevation angles and limited azimuths, respectively. The results show that in a typical situation, the TC and LC models achieve a similar performance. However, when the satellite signals are severely obstructed and few satellites are tracked, the float solution and ambiguity fixing rates in the LC model are dramatically decreased, while in the TC model, there are only minor declines and the difference in the ambiguity fixing rates can be as large as 30%. The correctly fixed ambiguity rates in the TC model also had an improvement of around 10%. Once the ambiguity was fixed, both models achieved a similar positioning accuracy.

Highlights

The Global Navigation Satellite System (GNSS) has entered into a new era in recent decades with four different systems operating simultaneously, i.e., American Global Positioning System (GPS), Russian GLObal NAvigation Satellite System (GLONASS), European Galileo, and Chinese BeiDou Navigation Satellite System (BDS), forming a joint multi-global navigation satellite systems (GNSSs) system
The virtual signal of the constant central frequency in the GLONASS system with a channel number of zero was introduced, and the inter-frequency phase bias (IFPB) and inter-system phase bias (ISPB) in GLONASS involving a tightly combined system were re-defined from the hardware delays
Based on this functional model, we proposed a practical algorithm to estimate the inter-frequency bias (IFB) rate and the inter-system bias (ISB), and their characteristics were analyzed using six pairs of available single-frequency multi-GNSS data of ultra-short and short baselines

Summary

Introduction

The Global Navigation Satellite System (GNSS) has entered into a new era in recent decades with four different systems operating simultaneously, i.e., American Global Positioning System (GPS), Russian GLObal NAvigation Satellite System (GLONASS), European Galileo, and Chinese BeiDou Navigation Satellite System (BDS), forming a joint multi-GNSS system. Since satellite signals may be obstructed by the surrounding huge buildings or a block of high buildings, the multi-GNSS system can provide the potential ability to resist the risk of satellite deficiency and retain a satisfactory positioning performance. How to integrate the observation data of different systems is a crucial issue toward realizing multi-GNSS precise positioning. In the case of popular relative positioning, such as real-time kinematic (RTK), there are two different models to realize the integration [3]. The first is to individually choose pivot satellites for different systems and undertake differencing between satellites within each system; this method is called the loose combination (LC). The other method is to choose only one pivot satellite for all systems and undertake differencing across different systems; this method is called the tight combination (TC) [4]

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Conclusion