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Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R): Techniques, Applications, and Challenges

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1029

Special Issue Editors


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Guest Editor
National Space Science Center, Chinese Academy of Sciences (NSSC/CAS), Beijing 100190, China
Interests: GNSS-R; ocean wind; data assimilation
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Interests: global navigation satellite system; earth observation; remote sensing
School of Electronic Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing, China
Interests: GNSS-R

Special Issue Information

Dear Colleagues,

The spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technique leverages L-band signals from existing GNSS satellites, offering significant advantages in terms of cost efficiency, penetration capability and high spatiotemporal resolution for Earth observation. Over the past decade,  a number of GNSS-R missions, including CYGNSS, SMAP-R, FSSCAT, Bufeng-1, FengYun-3 series, PRETTY and Triton, have successfully launched. In recent years, private companies such as Spire, Tianmu, Yunyao, and Muon have also developed or are developing small-satellite constellations, enhancing the GNSS-R landscape. New missions such as HydroGNSS and the next generation of FengYun-3 series are also expected to launch in the coming years. These missions, with different instrument and signal processing designs, such as multi-GNSS and polarimetry techniques, have provided valuable datasets for advancing GNSS-R research and applications.

This Special Issue on “Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R): Techniques, Applications, and Challenges” welcomes submissions related to spaceborne GNSS-R techniques including mission design, data applications, theoretical models and supporting experiments. 

We invite manuscripts on, but not limited to, the following topics:

  • Mission introduction
  • Instrument design, signal processing and calibration
  • Scattering model
  • Applications in ocean, land, cryosphere and ionosphere
  • Target detection and novel applications
  • Ground experiment that supports spaceborne missions
  • Synergies between spaceborne GNSS-R data with other remote sensing techniques
  • Data assimilation of spaceborne GNSS-R data

Dr. Feixiong Huang
Dr. Wei Wan
Dr. Feng Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • GNSS-R
  • satellite mission
  • small satellite
  • ocean surface
  • soil moisture
  • sea ice
  • biomass
  • target detection

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Published Papers (2 papers)

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Research

22 pages, 3162 KiB  
Article
On the Possibility of Detecting Evaporation Ducts Through GNSS Reflectometry
by Fu Li, Yueqiang Sun, Xianyi Wang, Junming Xia, Feixiong Huang, Qifei Du, Weihua Bai, Zhuoyan Wang and Tongsheng Qiu
Remote Sens. 2025, 17(8), 1420; https://doi.org/10.3390/rs17081420 - 16 Apr 2025
Viewed by 157
Abstract
An evaporation duct is a kind of atmospheric event with a refractive index exceeding the curvature of the Earth, which mostly exists on the ocean surface. Evaporation ducts have a great influence on radar, such as causing blind zones or achieving over-the-horizon detection. [...] Read more.
An evaporation duct is a kind of atmospheric event with a refractive index exceeding the curvature of the Earth, which mostly exists on the ocean surface. Evaporation ducts have a great influence on radar, such as causing blind zones or achieving over-the-horizon detection. However, there is a lack of effective technology for evaporation duct detection, especially for passive methods. Global Navigation Satellite System Reflectometry (GNSS-R) has demonstrated potential in various remote sensing applications. However, its utilization for evaporation duct retrieval has not yet been successfully achieved. This study investigates the impact of evaporation ducts on GNSS-R delay maps (DMs), demonstrating that they elevate the non-specular point region, with the extent of this rising zone correlating with the evaporation duct height (EDH). Through semi-physical simulation, the rise signal is modeled. During a four-day experiment, GPS-R DMs with obvious features of evaporation ducts were repeatedly observed. Additionally, this study attempts to find the maximum code delay in the experimental data. The EDH is retrieved using the maximum code delay and GPS elevation angle, exhibiting a 4 m error relative to the reference model under the condition that all effective waveforms are successfully received. The results demonstrate that the GNSS-R offers a promising passive method for evaporation duct detection. Full article
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22 pages, 13936 KiB  
Article
Multipath Effects Mitigation in Offshore Construction Platform GNSS-RTK Displacement Monitoring Using Parametric Temporal Convolution Network
by Yiyang Jiang, Cheng Guo, Jinfeng Wang and Rongqiao Xu
Remote Sens. 2025, 17(4), 601; https://doi.org/10.3390/rs17040601 - 10 Feb 2025
Viewed by 558
Abstract
The Global Navigation Satellite System (GNSS), renowned for its high precision and automation, has shone brightly in the deformation monitoring of offshore facilities and sea-crossing bridges. However, antennas placed in these locations are often subject to signal interference from various reflective surfaces, such [...] Read more.
The Global Navigation Satellite System (GNSS), renowned for its high precision and automation, has shone brightly in the deformation monitoring of offshore facilities and sea-crossing bridges. However, antennas placed in these locations are often subject to signal interference from various reflective surfaces, such as rivers and oceans, which significantly compromises observation accuracy and reliability. Synthesizing previous research, we first propose a method for multipath dataset construction, which involves GNSS observation linear combinations, detailed mapping of the near-field reflector, and employed static solution residuals as reference. Subsequently, we construct and train a corresponding para-TCN (parametric Temporal Convolution Network) to enable real-time prediction of multipath prediction. Through time domain and frequency domain analysis, it has been demonstrated that the trained network can capture the main features of multipath models and suppress those components in both the data distribution and frequency band, effectively mitigating the interference of multipath errors in observations. Full article
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