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1. Real-Time Loosely Coupled 3DMA GNSS/Doppler Measurements Integration Using a Graph Optimization and Its Performance Assessments in Urban Canyons of New York

   https://doi.org/10.3390/s22176533  

   Ng, Hoi-Fung; Hsu, Li-Ta; Lee, Max Jwo; Feng, Junchi; Naeimi, Tahereh; Beheshti, Mahya; Rizzo, John-Ross (September 2022, Sensors)

   Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad difficulties. Precise localization is still a gap in the field and is critical to safe navigation. Conventional GNSS positioning cannot provide satisfactory performance in urban canyons. 3D mapping-aided (3DMA) GNSS may serve as an urban GNSS solution, since the availability of 3D city models has widely increased. As a result, this study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms. Shadow matching was integrated with likelihood-based ranging 3DMA GNSS, generating positioning hypothesis candidates. To increase robustness, the 3DMA GNSS solution was then optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion. This study also evaluated positioning performance using an advanced wearable system’s recorded data in New York City. The real-time forward-processed FGO can provide a root-mean-square error (RMSE) of about 21 m. The RMSE drops to 16 m when the data is post-processed with FGO in a combined direction. Overall results show that the proposed loosely-coupled 3DMA FGO algorithm can provide a better and more robust positioning performance for the multi-sensor integration approach used by this wearable for persons with BLV. 

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2. A Dense Block Model Representing Western Continental United States Deformation for the 2023 Update to the National Seismic Hazard Model

   https://doi.org/10.1785/0220220141  

   Evans, Eileen L. (August 2022, Seismological Research Letters)

   Abstract Seismic hazard assessment, such as the U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM), relies on estimates of fault slip rate based on geology and/or geodetic observations such as the Global Navigation Satellite System (GNSS), including the Global Positioning System. Geodetic fault slip rates may be estimated within a 3D spherical block model, in which the crust is divided into microplates bounded by mapped faults; fault slip rates are determined by the relative rotations of adjacent microplates. Uncertainty in selecting appropriate block-bounding faults and in forming closed microplates has limited the interpretability of block models for seismic hazard modeling. By introducing an automated block closure algorithm and regularizing the resulting densely spaced block model with total variation regularization, I develop the densest and most complete block model of the western continental United States to date. The model includes 853 blocks bounded by 1017 geologically identified fault sections from the USGS NSHM Fault Sections database. Microplate rotations and fault slip rates are constrained by 4979 GNSS velocities and 1243 geologic slip rates. I identify a regularized solution that fits the GNSS velocity field with a root mean square misfit of 1.9 mm/yr and reproduces 57% of geologic slip rates within reported geologic uncertainty and model sensitivity, consistent with other geodetic-based models in this Focus Section. This block model includes slip on faults that are not included in the USGS NSHM Fault sections database (but are required to form closed blocks) for an estimate of “off-fault” deformation of 3.62×1019  N·m/yr, 56% of the total calculated moment accumulation rate in the model. 

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3. Shallow Water Seafloor Geodesy With Wave Glider‐Based GNSS‐Acoustic Surveying of a Single Transponder

   https://doi.org/10.1029/2023EA003043  

   Xie, Surui; Zumberge, Mark; Sasagawa, Glenn; Voytenko, Denis (October 2023, Earth and Space Science)

   Abstract Due to the blockage of seawater, seafloor displacement cannot be directly measured by space geodesy. The combination of Global Navigation Satellite Systems‐acoustic ranging (GNSS‐A) has been used to overcome the electromagnetic barrier, so that a GNSS‐determined sea surface vessel's coordinates can be transformed to seafloor benchmarks in a global reference frame. Due to the high cost and science priorities, previous GNSS‐A studies mainly targeted relatively deep water and a minimum of three transponders were used to form an array, equivalent to a precision geodetic station. With recent developments in unmanned autonomous surface vessels, low cost GNSS‐A surveys are poised to become practical. Here we demonstrate that with a carefully designed surveying trajectory, Wave Glider‐based GNSS‐A surveying of a single transponder in shallow water can provide centimeter‐level accuracy on horizontal seafloor positioning, even if the sound speed model deviates from the actual value by a few meters per second. Results from a nine‐month experiment conducted at ∼54 m water depth show that the repeatability of the seafloor horizontal positioning is better than 2 cm. When conditions allow, the acoustic observations should be collected symmetrically about the transponder and data redundancies are recommended to reduce the error associated with time‐dependent variations in sound speed. 

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4. High‐Density Integrated GNSS and Hydrologic Monitoring Network for Short‐Scale Hydrogeodesy in High Mountain Watersheds

   https://doi.org/10.1029/2022EA002678  

   White, Alissa M.; Lajoie, Lia J.; Knappe, Ellen; Martens, Hilary R.; Swarr, Matthew J.; Khatiwada, Ashlesha; Oliver, Brett; Perry, Mason; Clayton, Noah; Bendick, Rebecca; et al (October 2023, Earth and Space Science)

   Abstract We installed a purpose‐built network of co‐located Global Navigation Satellite System (GNSS) stations and meteorological instrumentation to investigate water storage in a high‐mountain watershed along the Idaho‐Montana border. Twelve GNSS stations are distributed across the Selway‐Lochsa watersheds at approximately 30–40 km spacing, filling a critical observational gap between localized point measurements and regional geodetic and satellite data sets. The unique coupling of geodetic and hydrologic observations in this network enables direct comparison between co‐located GNSS measurements of the elastic response of the solid Earth and local changes in measured water storage. This network is specifically designed to address questions of hydrologic storage and movement at the mountain watershed scale. Here, we describe technical details of the network and its deployment; introduce new hydrologic, meteorologic, and geodetic data sets recorded by the network; process and analyze the source data (e.g., time series of daily three‐dimensional GNSS site positions, removal of non‐hydrologic signals); and characterize basic empirical relationships between water storage, water movement, and GNSS‐inferred surface displacement. The network shows preliminary evidence for spatial differences in displacement resulting from a range of snow loads across elevations, but longer and more complete data records are needed to support these initial findings. We also provide examples of additional scientific applications of this network, including estimations of snow depth and snow water equivalent from GNSS multipath reflectometry. Finally, we consider the challenges, limitations, and opportunities of deploying GNSS and weather stations at high elevations with heavy snowpack and offer ideas for technical improvements. 

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5. Inferring Ice Fabric From Birefringence Loss in Airborne Radargrams: Application to the Eastern Shear Margin of Thwaites Glacier, West Antarctica

   https://doi.org/10.1029/2020JF006023  

   Young, T. J.; Schroeder, D. M.; Jordan, T. M.; Christoffersen, P.; Tulaczyk, S. M.; Culberg, R.; Bienert, N. L. (May 2021, Journal of Geophysical Research: Earth Surface)

   Abstract In airborne radargrams, undulating periodic patterns in amplitude that overprint traditional radiostratigraphic layering are occasionally observed, however, they have yet to be analyzed from a geophysical or glaciological perspective. We present evidence supported by theory that these depth‐periodic patterns are consistent with a modulation of the received radar power due to the birefringence of polar ice, and therefore indicate the presence of bulk fabric anisotropy. Here, we investigate the periodic component of birefringence‐induced radar power recorded in airborne radar data at the eastern shear margin of Thwaites Glacier and quantify the lateral variation in azimuthal fabric strength across this margin. We find the depth variability of birefringence periodicity crossing the shear margin to be a visual expression of its shear state and its development, which appears consistent with present‐day ice deformation. The morphology of the birefringent patterns is centered at the location of maximum shear and observed in all cross‐margin profiles, consistent with predictions of ice fabric when subjected to simple shear. The englacial fabric appears stronger inside the ice stream than outward of the shear margin. The detection of birefringent periodicity from non‐polarimetric radargrams presents a novel use of subsurface radar to constrain lateral variations in fabric strength, locate present and past shear margins, and characterize the deformation history of polar ice sheets. 

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