A Review on Multi-GNSS for Earth Observation and Emerging Applications

Author:

Jin ShuanggenORCID,Wang Qisheng,Dardanelli GinoORCID

Abstract

Global Navigation Satellite System (GNSS) has drawn the attention of scientists and users all over the world for its wide-ranging Earth observations and applications. Since the end of May 2022, more than 130 satellites are available for fully global operational satellite navigation systems, such as BeiDou Navigation Satellite System (BDS), Galileo, GLONASS and GPS, which have been widely used in positioning, navigation, and timing (PNT), e.g., precise orbit determination and location-based services. Recently, the refracted, reflected, and scattered signals from GNSS can remotely sense the Earth’s surface and atmosphere with potential applications in environmental remote sensing. In this paper, a review of multi-GNSS for Earth Observation and emerging application progress is presented, including GNSS positioning and orbiting, GNSS meteorology, GNSS ionosphere and space weather, GNSS-Reflectometry and GNSS earthquake monitoring, as well as GNSS integrated techniques for land and structural health monitoring. One of the most significant findings from this review is that, nowadays, GNSS is one of the best techniques in the field of Earth observation, not only for traditional positioning applications, but also for integrated remote sensing applications. With continuous improvements and developments in terms of performance, availability, modernization, and hybridizing, multi-GNSS will become a milestone for Earth observations and future applications.

Funder

National Natural Science Foundation of China

Shanghai Leading Talent Project

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference126 articles.

1. BDS http://www.csno-tarc.cn/en/system/constellation

2. Galileo https://www.gsc-europa.eu/system-service-status/constellation-information

3. GLONASS https://www.glonass-iac.ru/en/sostavOG

4. GPS

5. GNSS Atmospheric Seismology: Theory, Observations and Modeling;Jin,2019

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