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Special Issue "High-Precision GNSS in Remote Sensing Applications"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (30 November 2018)

Special Issue Editor

Guest Editor
Dr. Sandra Verhagen

Geoscience and Remote Sensing, Civil Engineering and Geosciences Faculty, TU Delft, the Netherlands
Website | E-Mail
Interests: GNSS; mathematical geodesy; multi-GNSS modelling (PPP, PPP-RTK, NRTK); tropospheric and ionospheric delays; quality control and integrity

Special Issue Information

Dear Colleagues,

Global Navigation Satellite Systems (GNSS) have found widespread use, not only for position determination, but also, more and more, for a wide range of remote sensing applications. In those applications, GNSS observations are used for determining physical parameters that are of interest to Earth sciences.

You are invited to contribute to this Special Issue to present advances and challenges in the field of high-precision GNSS remote sensing regarding concepts/principles, signal and data processing, error modelling, modelling of geophysical processes, and performance in terms of availability, continuity, accuracy and integrity.

Topics may include, but are not limited to:

GNSS reflectometry (ocean/lake levels, sea state, soil moisture, vegetation, snow depth);
Atmospheric sounding (troposphere and ionosphere, weather forecasts, climate research);
Geohazard monitoring/alarm systems (landslides, earthquakes, volcanoes, tsunamis);
Surface deformation (land uplift, crustal deformation, glacier motion, man-induced subsidence);
Ocean currents and tides;
Animal tracking

Dr. Sandra Verhagen
Guest Editor

Manuscript Submission Information

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Keywords

  • GNSS remote sensing
  • GNSS reflectometry
  • Signal and data processing
  • Error modelling
  • Deformation
  • Geohazards
  • Atmosphere and climate studies
  • Ocean level and sea states
  • Soil moisture

Published Papers (13 papers)

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Research

Open AccessArticle Low-Cost GNSS-R Altimetry on a UAV for Water-Level Measurements at Arbitrary Times and Locations
Sensors 2019, 19(5), 998; https://doi.org/10.3390/s19050998
Received: 1 December 2018 / Revised: 16 February 2019 / Accepted: 20 February 2019 / Published: 26 February 2019
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Abstract
Together with direct Global Navigation Satellite System (GNSS) signals, the signals reflected at the water surface can be received by an unmanned aerial vehicle (UAV). From the range difference between two GNSS signal paths, the height of the UAV above the water level [...] Read more.
Together with direct Global Navigation Satellite System (GNSS) signals, the signals reflected at the water surface can be received by an unmanned aerial vehicle (UAV). From the range difference between two GNSS signal paths, the height of the UAV above the water level can be geometrically estimated using the weighted least squares method, called GNSS reflectometry (GNSS-R) altimetry. Experimental low-cost GNSS-R altimetry flights with a UAV were conducted at the coast of Lake Biwa, Japan. Although the height estimated by the GNSS-R altimeter included large short-term noises up to 8 m amplitude, it agreed well with the UAV altitude measured by the post-processed kinematic positioning. By selecting better weight functions in the least square method and using sufficient temporal averaging, the GNSS-R altimetry achieved accuracy in the order of 0.01 m if a sufficient number of GNSS satellites with high elevation angles were available. The dependency of the results on the weight functions is also discussed. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle A New Method for Refining the GNSS-Derived Precipitable Water Vapor Map
Sensors 2019, 19(3), 698; https://doi.org/10.3390/s19030698
Received: 18 December 2018 / Revised: 3 February 2019 / Accepted: 5 February 2019 / Published: 8 February 2019
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Abstract
The objective of the study was to put forth an interpolation method (the LZ method) for refining the GNSS-derived precipitable water vapor (PWV) map. We established a regional weighted mean temperature (Tm) model for this experiment, which introduced a minor [...] Read more.
The objective of the study was to put forth an interpolation method (the LZ method) for refining the GNSS-derived precipitable water vapor (PWV) map. We established a regional weighted mean temperature (Tm) model for this experiment, which introduced a minor difference into the resultant GNSS-derived PWV compared to the previous Tm models. The kernel of the LZ method consists of increasing the sample density via the virtual sample points. These virtual sample points originated from the digital elevation model (DEM) were constructed on the basis of the statistically significant correlation between PWV and geographical location (i.e., geographical coordinates and elevation). The LZ method was validated and compared to the conventional interpolation approach only accounting for the original sample points. The results reflect that the PWV maps generated by the LZ method showed more details than through conventional one. In addition, the prediction performance of the LZ method was better than that of the conventional method by using cross-validation. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle Improving GNSS PPP Convergence: The Case of Atmospheric-Constrained, Multi-GNSS PPP-AR
Sensors 2019, 19(3), 587; https://doi.org/10.3390/s19030587
Received: 1 December 2018 / Revised: 17 January 2019 / Accepted: 24 January 2019 / Published: 30 January 2019
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Abstract
GNSS positioning performance has been shown to improve with the ingestion of data from Global Ionospheric Maps (GIMs) and tropospheric zenith path delays, which are produced by, e.g., the International GNSS Service (IGS). For both dual- and triple-frequency Precise Point Positioning (PPP) processing, [...] Read more.
GNSS positioning performance has been shown to improve with the ingestion of data from Global Ionospheric Maps (GIMs) and tropospheric zenith path delays, which are produced by, e.g., the International GNSS Service (IGS). For both dual- and triple-frequency Precise Point Positioning (PPP) processing, the significance of GIM and tropospheric products in processing is not obvious in the quality of the solution after a few hours. However, constraining the atmosphere improves PPP initialization and solution convergence in the first few minutes of processing. The general research question to be answered is whether there is any significant benefit in constraining the atmosphere in multi-frequency PPP? A key related question is: regarding time and position accuracy, how close are we to RTK performance in the age of multi-GNSS PPP-AR? To address these questions, this paper provides insight into the conceptual analyses of atmospheric GNSS PPP constraints. Dual- and triple-frequency scenarios were investigated. Over 60% improvement in convergence time was observed when atmospheric constraints are applied to a dual-frequency multi-GNSS PPP-AR solution. Future work would involve employing the constraints to improve low-cost PPP solutions. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China
Sensors 2019, 19(3), 541; https://doi.org/10.3390/s19030541
Received: 18 November 2018 / Revised: 23 January 2019 / Accepted: 24 January 2019 / Published: 28 January 2019
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Abstract
In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the [...] Read more.
In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the movement velocity of the buoy using the Doppler frequency shift of satellite GPS signals, and then to calculate the wave parameters from the movement velocity according to ocean wave theory. The shortage of the GPS wave buoy is the occasional occurrence of some unusual values in the movement velocity. This is mainly due to the fact that the GPS antenna is occasionally covered by sea water and cannot normally receive high-quality satellite GPS signals. The traditional solution is to remove these unusual movement velocity values from the records, which requires furthering extend the acquisition time of satellite GPS signals to ensure there is a large enough quantity of effective movement velocity values. Based on the traditional GPS wave measurement technology, this paper presents the algorithmic flow and proposes two improvement measures. On the one hand, the neural network algorithm is used to correct the unusual movement velocity data so that extending the acquisition time of satellite GPS signals is not necessary and battery power is saved. On the other hand, the Gaussian low-pass filter is used to correct the raw directional wave spectrum, which can further eliminate the influence of noise spectrum energy and improve the measurement accuracy. The on-site sea test of the SBF7-1A GPS wave buoy, developed by the National Ocean Technology Center in China, and the gravity-acceleration-type DWR-MKIII Waverider buoy are highlighted in this article. The wave data acquired by the two buoys are analyzed and processed. It can be seen from the processed results that the ocean wave parameters from the two kinds of wave buoys, such as wave height, wave period, wave direction, wave frequency spectrum, and directional wave spectrum, are in good consistency, indicating that the SBF7-1A GPS wave buoy is comparable to the traditional gravity-acceleration-type wave buoy in terms of its accuracy. Therefore, the feasibility and validity of the two improvement measures proposed in this paper are confirmed. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle BeiDou Augmented Navigation from Low Earth Orbit Satellites
Sensors 2019, 19(1), 198; https://doi.org/10.3390/s19010198
Received: 16 November 2018 / Revised: 20 December 2018 / Accepted: 26 December 2018 / Published: 7 January 2019
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Abstract
Currently, the Global Navigation Satellite System (GNSS) mainly uses the satellites in Medium Earth Orbit (MEO) to provide position, navigation, and timing (PNT) service. The weak navigation signals limit its usage in deep attenuation environments, and make it easy to interference and counterfeit [...] Read more.
Currently, the Global Navigation Satellite System (GNSS) mainly uses the satellites in Medium Earth Orbit (MEO) to provide position, navigation, and timing (PNT) service. The weak navigation signals limit its usage in deep attenuation environments, and make it easy to interference and counterfeit by jammers or spoofers. Moreover, being far away to the Earth results in relatively slow motion of the satellites in the sky and geometric change, making long time needed for achieved centimeter positioning accuracy. By using the satellites in Lower Earth Orbit (LEO) as the navigation satellites, these disadvantages can be addressed. In this contribution, the advantages of navigation from LEO constellation has been investigated and analyzed theoretically. The space segment of global Chinese BeiDou Navigation Satellite System consisting of three GEO, three IGSO, and 24 MEO satellites has been simulated with a LEO constellation with 120 satellites in 10 orbit planes with inclination of 55 degrees in a nearly circular orbit (eccentricity about 0.000001) at an approximate altitude of 975 km. With simulated data, the performance of LEO constellation to augment the global Chinese BeiDou Navigation Satellite System (BeiDou-3) has been assessed, as one of the example to show the promising of using LEO as navigation system. The results demonstrate that the satellite visibility and position dilution of precision have been significantly improved, particularly in mid-latitude region of Asia-Pacific region, once the LEO data were combined with BeiDou-3 for navigation. Most importantly, the convergence time for Precise Point Positioning (PPP) can be shorted from about 30 min to 1 min, which is essential and promising for real-time PPP application. Considering there are a plenty of commercial LEO communication constellation with hundreds or thousands of satellites, navigation from LEO will be an economic and promising way to change the heavily relay on GNSS systems. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle The Marine Boundary Layer Height over the Western North Pacific Based on GPS Radio Occultation, Island Soundings, and Numerical Models
Sensors 2019, 19(1), 155; https://doi.org/10.3390/s19010155
Received: 12 November 2018 / Revised: 21 December 2018 / Accepted: 28 December 2018 / Published: 4 January 2019
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Abstract
This paper estimates marine boundary layer height (MBLH) over the western North Pacific (WNP) based on Global Positioning System Radio Occultation (GPS-RO) profiles from the Formosa Satellite Mission 3 (FORMOSAT-3)/Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites, island soundings, and numerical [...] Read more.
This paper estimates marine boundary layer height (MBLH) over the western North Pacific (WNP) based on Global Positioning System Radio Occultation (GPS-RO) profiles from the Formosa Satellite Mission 3 (FORMOSAT-3)/Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites, island soundings, and numerical models. The seasonally-averaged MBLHs computed from nine years (2007–2015) of GPS-RO data are inter-compared with those obtained from sounding observations at 15 island stations and from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA-Interim) and National Centers for Environmental Prediction Global Forecast System (NCEP GFS) data over the WNP from 2012 to 2015. It is found that the MBLH using nine years of GPS-RO data is smoother and more consistent with that obtained from sounding observations than is the MBLH using four years of GPS-RO data in a previous study. In winter, higher MBLHs are found around the subtropical latitudes and over oceans east of Japan, which are approximately located within the paths of the North Equatorial Current and the Kuroshio Current. The MBLH is also significantly higher in winter than in summer over the WNP. The above MBLH pattern is generally similar to those obtained from the analysis data of the ERA-Interim and NCEP GFS, but the heights are about 200 m higher. The verification with soundings suggests that the ERA-Interim has a better MBLH estimation than the NCEP GFS. Thus, the MBLH distributions obtained from both the nine-year GPS-RO and the ERA-Interim data can represent well the climatological MBLH over the WNP, but the heights should be adjusted about 30 m lower for the former and ~200 m higher for the latter. A positive correlation between the MBLH and the instability of the lower atmosphere exists over large near-shore areas of the WNP, where cold air can move over warm oceans from the land in winter, resulting in an increase in lower-atmospheric instability and providing favorable conditions for convection to yield a higher MBLH. During summer, the lower-atmospheric instability becomes smaller and the MBLH is thus lower over near-shore oceans. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle Combination of High- and Low-Rate GPS Receivers for Monitoring Wind-Induced Response of Tall Buildings
Sensors 2018, 18(12), 4100; https://doi.org/10.3390/s18124100
Received: 30 September 2018 / Revised: 6 November 2018 / Accepted: 21 November 2018 / Published: 23 November 2018
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Abstract
High-rise buildings are susceptible to wind-induced displacements, which can be precisely monitored by using GPS technology. However, GPS monitoring applications may be subject to signal interference and high hardware costs. This study presents a new wind-induced vibration monitoring approach that is based on [...] Read more.
High-rise buildings are susceptible to wind-induced displacements, which can be precisely monitored by using GPS technology. However, GPS monitoring applications may be subject to signal interference and high hardware costs. This study presents a new wind-induced vibration monitoring approach that is based on the mixed use of high-rate and low-rate GPS receivers. In the proposed approach, high-rate receivers are only required in the monitoring stations, where we apply time-differenced positioning to obtain position changes between adjacent epochs. The derived high-rate monitoring station position changes are then integrated with low-rate single epoch relative positioning results between the monitoring and reference stations. Experimental results with both simulated and real data show that the proposed method has a comparable performance with the traditional relative positioning approach, in terms of determining buildings’ vibration frequency, displacement, and acceleration. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle Precipitable Water Vapour Retrieval from GPS Precise Point Positioning and NCEP CFSv2 Dataset during Typhoon Events
Sensors 2018, 18(11), 3831; https://doi.org/10.3390/s18113831
Received: 7 October 2018 / Revised: 31 October 2018 / Accepted: 5 November 2018 / Published: 8 November 2018
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Abstract
Radiosonde is extensively used for understanding meteorological parameters in the vertical direction. Four typhoon events, including three landfalls (MERANTI, NEPARTAK, and MEGI) and one non-landfall (MALAKAS), were chosen in analysing the precipitable water vapour (PWV) characteristics in this study. The spatial distribution of [...] Read more.
Radiosonde is extensively used for understanding meteorological parameters in the vertical direction. Four typhoon events, including three landfalls (MERANTI, NEPARTAK, and MEGI) and one non-landfall (MALAKAS), were chosen in analysing the precipitable water vapour (PWV) characteristics in this study. The spatial distribution of the three radiosonde stations in Zhejiang province does not meet the requirement in analysing changes in PWV during typhoon event. Global position system (GPS) observations are an alternative method for deriving the PWV. This enables improvements in the temporal–spatial resolution of PWV computed by the radiosonde measurements. The National Centers for Environmental Prediction (NCEP) re-analysed data were employed for interpolating temperature and atmosphere pressure at the GPS antennas height. The PWV computed from GPS observations and NCEP re-analysed data were then compared with the true PWV. The maximum difference of radiosonde and GPS PWV was not more than 30 mm at Taiz station. The Root-Mean-Square (RMS) of PWV differences between radiosonde and GPS was not more than 5 mm in January, February, March, November, and December. It was slightly greater than 5 mm in April. High RMS in May, June, July, August, September, and October implies that differences in GPS and radiosonde PWVs are evident in these months. Correlation coefficients of GPS and radiosonde PWVs were more than 0.9, indicating that the changes in GPS and radiosonde PWVs are similar. Radiosonde calculated PWVs were used for GPS PWV calibration for understanding the PWV changes during the period of a typhoon event. The results from three landfall typhoons show that the average PWV over Zhejiang province is increasing and approaching China mainland. In contrast, MALAKAS did not make landfall and shows a decreasing PWV trend, although it was heading to China mainland. Generally, the PWV change can be used to predict whether the typhoon will make landfall in these cases. PWV spatial distribution of MERANTI shows that PWV peaks change along the typhoon epicenter over Zhejiang province. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle Stand-Alone GNSS Sensors as Velocity Seismometers: Real-Time Monitoring and Earthquake Detection
Sensors 2018, 18(11), 3712; https://doi.org/10.3390/s18113712
Received: 10 October 2018 / Revised: 29 October 2018 / Accepted: 30 October 2018 / Published: 31 October 2018
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Abstract
By means of the time derivatives of Global Navigation Satellite System (GNSS) carrier-phase measurements, the instantaneous velocity of a stand-alone, single GNSS receiver can be estimated with a high precision of a few mm/s; it is feasible to even obtain the level of [...] Read more.
By means of the time derivatives of Global Navigation Satellite System (GNSS) carrier-phase measurements, the instantaneous velocity of a stand-alone, single GNSS receiver can be estimated with a high precision of a few mm/s; it is feasible to even obtain the level of tenths of mm/s. Therefore, only data from the satellite navigation message are needed, thus discarding any data from a reference network. Combining this method with an efficient movement-detection algorithm opens some interesting applications for geohazard monitoring; an example is the detection of strong earthquakes. This capability is demonstrated for a case study of the 6.5 Mw earthquake of October 30, 2016, near the city of Norcia in Italy; in that region, there are densely deployed GNSS stations. It is shown that GNSS sensors can detect seismic compressional (P) waves, which are the first to arrive at a measurement station. These findings are substantiated by a comparison with data of strong-motion (SM) seismometers. Furthermore, it is shown that the GNSS-only hypocenter localization comes close (less than a kilometer) to the solutions provided by official seismic services. Finally, we conclude that this method can provide important contributions to a real-time geohazard early-warning system. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle Positioning Performance of BDS Observation of the Crustal Movement Observation Network of China and Its Potential Application on Crustal Deformation
Sensors 2018, 18(10), 3353; https://doi.org/10.3390/s18103353
Received: 10 September 2018 / Revised: 4 October 2018 / Accepted: 4 October 2018 / Published: 8 October 2018
Cited by 2 | PDF Full-text (2618 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The Crustal Movement Observation Network of China (CMONOC) has begun receiving BeiDou Navigation Satellite System (BDS) observations since 2015, and accumulated more than 2.5 years of data. BDS observations has been widely applied in many fields, and long-term continuous data provide a new [...] Read more.
The Crustal Movement Observation Network of China (CMONOC) has begun receiving BeiDou Navigation Satellite System (BDS) observations since 2015, and accumulated more than 2.5 years of data. BDS observations has been widely applied in many fields, and long-term continuous data provide a new strategy for the study of crustal deformation in China. This paper focuses on the evaluation of BDS positioning performance and its potential application on crustal deformation in CMONOC. According to the comparative analysis on multipath delay (MPD) and signal to noise ratio (SNR) between BDS and GPS data, the data quality of BDS is at the same level with GPS measurements in COMONC. The spatial distribution of BDS positioning accuracy evaluated as the root mean square (RMS) of daily residual position time series on horizontal component is latitude-dependent, declining with the increasing of station latitude, while the vertical one is randomly distributed in China. The mean RMS of BDS position residual time series is 7 mm and 22 mm on horizontal and vertical components, respectively, and annual periodicity in position time series can be identified by BDS data. In view of the accuracy of BDS positioning, there are no systematic differences between GPS and BDS results. Based on time series analysis with data volume being 2.5 years, the noise characteristics of BDS daily position time series is time-correlated and corresponding noise is white plus flicker noise model, and the derived mean RMS of the BDS velocities is 1.2, 1.5, and 4.1 mm/year on north, east, and up components, respectively. The imperfect performance of BDS positioning relative to GPS is likely attributed to the relatively low accuracy of BDS ephemeris, and the sparse amount of MEO satellites distribution in the BDS constellation. It is expectable to study crustal deformation in CMONOC by BDS with the gradual maturity of its constellation and the accumulation of observations. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle A Novel Wind Speed Estimation Based on the Integration of an Artificial Neural Network and a Particle Filter Using BeiDou GEO Reflectometry
Sensors 2018, 18(10), 3350; https://doi.org/10.3390/s18103350
Received: 9 September 2018 / Revised: 23 September 2018 / Accepted: 28 September 2018 / Published: 8 October 2018
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Abstract
Oceanographic remote sensing, which is based on the sensitivity of reflected signals from the Global Navigation Satellite Systems (GNSS), so-called GNSS-Reflectometry (GNSS-R), is very useful for the observation of ocean wind speed. Wind speed estimation over the ocean is the core factor in [...] Read more.
Oceanographic remote sensing, which is based on the sensitivity of reflected signals from the Global Navigation Satellite Systems (GNSS), so-called GNSS-Reflectometry (GNSS-R), is very useful for the observation of ocean wind speed. Wind speed estimation over the ocean is the core factor in maritime transportation management and the study of climate change. The main concept of the GNSS-R technique is using the different times between the reflected and the direct signals to measure the wind speed and wind direction. Accordingly, this research proposes a novel technique for wind speed estimation involving the integration of an artificial neural network and the particle filter based on a theoretical model. Moreover, particle swarm optimization was applied to find the optimal weight and bias of the artificial neural network, in order to improve the accuracy of the estimation result. The observation dataset of the reflected signal information from BeiDou Geostationary Earth Orbit (GEO) satellite number 4 was used as an input for the estimation model. The data consisted of two phases with I and Q components. Two periods of BeiDou data were selected, the first period was from 3 to 8 August 2013 and the second period was from 12 to 14 August 2013, which corresponded to events from the typhoon Utor. The in situ wind speed measurement collected from the buoy station was used to validate the results. A coastal experiment was conducted at the Yangjiang site located in the South China Sea. The results show the ability of the proposed technique to estimate wind speed with a root mean square error of approximately 1.9 m/s. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography
Sensors 2018, 18(8), 2526; https://doi.org/10.3390/s18082526
Received: 18 June 2018 / Revised: 28 July 2018 / Accepted: 30 July 2018 / Published: 2 August 2018
Cited by 2 | PDF Full-text (8172 KB) | HTML Full-text | XML Full-text
Abstract
Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water [...] Read more.
Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water vapor distribution using GNSS observation data, plays an increasingly important role in GNSS meteorology. In this paper, a method to improve the distribution of observations in GNSS water vapor tomography is proposed to overcome the problem of the relatively concentrated distribution of observations, enable satellite signal rays to penetrate more tomographic voxels, and improve the issue of overabundance of zero elements in a tomographic matrix. Numerical results indicate that the accuracy of the water vapor tomography is improved by the proposed method when the slant water vapor calculated by GAMIT is used as a reference. Comparative results of precipitable water vapor (PWV) and water vapor density (WVD) profiles from radiosonde station data indicate that the proposed method is superior to the conventional method in terms of the mean absolute error (MAE), standard deviations (STD), and root-mean-square error (RMS). Further discussion shows that the ill-condition of tomographic equation and the richness of data in the tomographic model need to be discussed separately. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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Open AccessArticle A New Azimuth-Dependent Elevation Weight (ADEW) Model for Real-Time Deformation Monitoring in Complex Environment by Multi-GNSS
Sensors 2018, 18(8), 2473; https://doi.org/10.3390/s18082473
Received: 2 July 2018 / Revised: 24 July 2018 / Accepted: 30 July 2018 / Published: 31 July 2018
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Abstract
Global navigation satellite systems (GNSS) have provided an excellent way to monitor micro-deformation in real-time. However, at local sites where landslides frequently occur, the environment can include complex surroundings with mountains, dense vegetation, and human settlements, which can severely degrade the accuracy of [...] Read more.
Global navigation satellite systems (GNSS) have provided an excellent way to monitor micro-deformation in real-time. However, at local sites where landslides frequently occur, the environment can include complex surroundings with mountains, dense vegetation, and human settlements, which can severely degrade the accuracy of positioning with the GNSS technique. In this study, we propose an azimuth-dependent elevation weight (ADEW) model using an azimuth-dependent elevation mask (ADEM) to reduce the effects of multipath errors and improve the accuracy of real-time deformation monitoring in such environments. We developed an adaptive fixed-elevation mask to serve as the outlier of low precision observations at lower elevations for the ADEM, and then, we applied the weighted phase observations into the mitigation process for the effects of multipath errors. The real numerical results indicate that the ADEM model performs better than the conventional model, and the average improvements were 18.91% and 34.93% in the horizontal and vertical direction, respectively. The ADEW model further improved upon the ADEM model results by an additional 21.9% and 29.8% in the horizontal and vertical direction, respectively. Therefore, we propose that the ADEW model can significantly mitigate the effects of multipath errors and improve the accuracy of micro-deformation monitoring via GNSS receivers. Full article
(This article belongs to the Special Issue High-Precision GNSS in Remote Sensing Applications)
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