scholarly journals Improving GNSS-R Sea Surface Altimetry Precision Based on the Novel Dual Circularly Polarized Phased Array Antenna Model

2021 ◽  
Vol 13 (15) ◽  
pp. 2974
Author(s):  
Zhen Cui ◽  
Wei Zheng ◽  
Fan Wu ◽  
Xiaoping Li ◽  
Cheng Zhu ◽  
...  
Keyword(s):  
High Precision ◽  
Spatial Resolution ◽  
Measurement Accuracy ◽  
Phased Array ◽  
High Spatial Resolution ◽  
Beam Width ◽  
Sea Surface ◽  
Antenna Gain ◽  
Phased Array Antenna ◽  
Circularly Polarized

Antenna is one of the key payloads of the GNSS-R system, and the gain is an important performance parameter. The signal-to-noise ratio (SNR) of the received signal can be improved by increasing the gain of the GNSS-R antenna, therefore the measurement accuracy is improved. However, the antenna gain and its beam width, these two performance parameters, are contradictory. If the gain of the antenna is increased, its beam width will inevitably become narrower. This narrowed beam width will affect the width of the survey strip for the GNSS-R system, which cannot meet the requirement of the high-precision and high-spatial resolution spaceborne GNSS-R sea surface altimetry in the future. In this paper, a novel dual circularly polarized phased array antenna (NDCPPA) is proposed and investigated. First, the GNSS-R satellites currently operating in orbit are all cGNSS-R systems, which use the traditional element antenna (TEA) method for measurement. The antenna used in this method is with low gain, which limits the improvement of sea surface measurement accuracy. In response to this problem, this paper establishes an NDCPPA model of iGNSS-R measurement system based on the theory of coherent signal processing on the sea surface. This model uses the high-gain scanning beam to increase the gain of the iGNSS-R antenna without affecting its coverage area, thereby improving the sea surface altimetry precision. Second, in order to verify the gain improvement effect brought by adopting the NDCPPA model, an NDCPPA model verification prototype for iGNSS-R sea surface altimetry was designed and fabricated, and then measured in a microwave anechoic chamber. The measurement results show that, compared with the TEA method, the antenna gain of our proposed verification prototype is enhanced by 9.5 dB. And the measured and designed value of the gain of the verification prototype matches well. Third, based on the GPS L1 signal, the NDCPPA model is used to analyze the effect of improving the precision of sea surface altimetry. Compared with the TEA method, the proposed model can increase the altimetric precision of the nadir point from 7.27 m to 0.21 m, which effectively improves the performance of the iGNSS-R altimetry. The NDCPPA model proposed in this article can provide the theoretical method basis and the crucial technical support for the future high-precision and high-spatial-resolution GNSS-R sea surface altimetry verification satellite.

scholarly journals Increasing the Number of Sea Surface Reflected Signals Received by GNSS-Reflectometry Altimetry Satellite Using the Nadir Antenna Observation Capability Optimization Method

2019 ◽  
Vol 11 (21) ◽  
pp. 2473
Author(s):  
Liu ◽  
Zheng ◽  
Wu ◽  
Kang ◽  
Li ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Electromagnetic Scattering ◽  
Elevation Angle ◽  
Beam Width ◽  
Optimization Method ◽  
Satellite System ◽  
Sea Surface ◽  
Antenna Gain ◽  
Sea Surface Topography ◽  
Reflected Signal

High spatial resolution Global Navigation Satellite System-Reflectometry (GNSS-R) sea surface altimetry is of great significance for extracting precise information from sea surface topography. The nadir antenna is one of the key payloads for the GNSS-R altimetry satellite to capture and track the sea surface GNSS reflected signal. The observation capability of the nadir antenna directly determines the number of received reflected signals, which, in turn, affects the spatial resolution of the GNSS-R altimetry. The parameters affecting the ability of the nadir antenna to receive the reflected signal mainly include antenna gain, half-power beam width (HPBW), and pointing angle. Thus far, there are rarely studies on the observation capability of GNSS-R satellite nadir antenna. The design of operational satellite antenna does not fully combine the above three parameters to optimize the design of GNSS-R nadir antenna. Therefore, it is necessary to establish a GNSS-R spaceborne nadir antenna observation capability optimization method. This is the key to improving the number of sea surface reflected signals received by the GNSS-R altimeter satellites, thereby increasing the spatial resolution of the altimetry. This paper has carried out the following research on this. Firstly, based on the GNSS-R geometric relationship and signal processing theory, the nadir antenna signal-to-noise ratio model (NASNRM) with the gain and the elevation angle at the specular point (SP) as the main parameters is established. The accuracy of the model was verified using TechDemoSat-1 (TDS-1) observations. Secondly, based on the theory of electromagnetic scattering, considering the influence of HPBW and pointing angle on the antenna footprint size, a specular point filtering algorithm (SPFA) is proposed. Combined with the results obtained by NASNRM, the number of available specular points (SPs) is counted. The results show that as the antenna gain and the nadir-pointing angle increase, the number of SPs can reach a peak and then gradually decrease. Thirdly, combined with NASNRM and SPSA, a nadir antenna observation capability optimization method (NAOCOM) is proposed. The nadir antenna observation capability is characterized through the reflected signal utilization, and the results obtained by the method are used to optimize the combination of nadir antenna parameters. The research shows that when the orbital height of the GNSS-R satellite is 635 km, the optimal combination of nadir antenna parameters is 20.94 dBi for the gain and 32.82 degrees for the nadir-pointing angle, which can increase the observation capability of the TDS-1 satellite nadir antenna by up to 5.38 times.

Measurement accuracy and Cerenkov removal for high performance, high spatial resolution scintillation dosimetry

2005 ◽  
Vol 33 (1) ◽  
pp. 128-135 ◽  
Author(s):  
Louis Archambault ◽  
A. Sam Beddar ◽  
Luc Gingras ◽  
René Roy ◽  
Luc Beaulieu
Keyword(s):  
Spatial Resolution ◽  
High Performance ◽  
Measurement Accuracy ◽  
High Spatial Resolution

scholarly journals Insights into (U)HP metamorphism of the Western Gneiss Region, Norway: A high-spatial resolution and high-precision zircon study

2015 ◽  
Vol 414 ◽  
pp. 138-155 ◽  
Author(s):  
Joel W. DesOrmeau ◽  
Stacia M. Gordon ◽  
Andrew R.C. Kylander-Clark ◽  
Bradley R. Hacker ◽  
Samuel A. Bowring ◽  
...  
Keyword(s):  
High Precision ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Western Gneiss Region ◽  
Hp Metamorphism

scholarly journals Bathymetry Time Series Using High Spatial Resolution Satellite Images

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 531 ◽  
Author(s):  
Manuel Erena ◽  
José A. Domínguez ◽  
Joaquín F. Atenza ◽  
Sandra García-Galiano ◽  
Juan Soria ◽  
...  
Keyword(s):  
High Precision ◽  
Spatial Resolution ◽  
Satellite Images ◽  
Environmental Variability ◽  
High Spatial Resolution ◽  
Numerical Models ◽  
Three Dimensional ◽  
Satellite System ◽  
Precision Data ◽  
Mar Menor

The use of the new generation of remote sensors, such as echo sounders and Global Navigation Satellite System (GNSS) receivers with differential correction installed in a drone, allows the acquisition of high-precision data in areas of shallow water, as in the case of the channel of the Encañizadas in the Mar Menor lagoon. This high precision information is the first step to develop the methodology to monitor the bathymetry of the Mar Menor channels. The use of high spatial resolution satellite images is the solution for monitoring many hydrological changes and it is the basis of the three-dimensional (3D) numerical models used to study transport over time, environmental variability, and water ecosystem complexity.

scholarly journals FEASIBILITY STUDY OF LANDSAT-8 IMAGERY FOR RETRIEVING SEA SURFACE TEMPERATURE (CASE STUDY PERSIAN GULF)

2016 ◽  
Vol XLI-B8 ◽  
pp. 1107-1110
Author(s):  
F. Bayat ◽  
M. Hasanlou
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Real Time ◽  
Spatial Resolution ◽  
Persian Gulf ◽  
High Spatial Resolution ◽  
Sea Surface ◽  
Landsat 8 ◽  
Spectral Bands ◽  
Sst Retrieval

Sea surface temperature (SST) is one of the critical parameters in marine meteorology and oceanography. The SST datasets are incorporated as conditions for ocean and atmosphere models. The SST needs to be investigated for various scientific phenomenon such as salinity, potential fishing zone, sea level rise, upwelling, eddies, cyclone predictions. On the other hands, high spatial resolution SST maps can illustrate eddies and sea surface currents. Also, near real time producing of SST map is suitable for weather forecasting and fishery applications. Therefore satellite remote sensing with wide coverage of data acquisition capability can use as real time tools for producing SST dataset. Satellite sensor such as AVHRR, MODIS and SeaWIFS are capable of extracting brightness values at different thermal spectral bands. These brightness temperatures are the sole input for the SST retrieval algorithms. Recently, Landsat-8 successfully launched and accessible with two instruments on-board: (1) the Operational Land Imager (OLI) with nine spectral bands in the visual, near infrared, and the shortwave infrared spectral regions; and (2) the Thermal Infrared Sensor (TIRS) with two spectral bands in the long wavelength infrared. The two TIRS bands were selected to enable the atmospheric correction of the thermal data using a split window algorithm (SWA). The TIRS instrument is one of the major payloads aboard this satellite which can observe the sea surface by using the split-window thermal infrared channels (CH10: 10.6 μm to 11.2 μm; CH11: 11.5 μm to 12.5 μm) at a resolution of 30 m. The TIRS sensors have three main advantages comparing with other previous sensors. First, the TIRS has two thermal bands in the atmospheric window that provide a new SST retrieval opportunity using the widely used split-window (SW) algorithm rather than the single channel method. Second, the spectral filters of TIRS two bands present narrower bandwidth than that of the thermal band on board on previous Landsat sensors. Third, TIRS is one of the best space born and high spatial resolution with 30&thinsp;m. in this regards, Landsat-8 can use the Split-Window (SW) algorithm for retrieving SST dataset. Although several SWs have been developed to use with other sensors, some adaptations are required in order to implement them for the TIRS spectral bands. Therefore, the objective of this paper is to develop a SW, adapted for use with Landsat-8 TIRS data, along with its accuracy assessment. In this research, that has been done for modelling SST using thermal Landsat 8-imagery of the Persian Gulf. Therefore, by incorporating contemporary in situ data and SST map estimated from other sensors like MODIS, we examine our proposed method with coefficient of determination (R2) and root mean square error (RMSE) on check point to model SST retrieval for Landsat-8 imagery. Extracted results for implementing different SW's clearly shows superiority of utilized method by R<sup>2</sup>&thinsp;=&thinsp;0.95 and RMSE&thinsp;=&thinsp;0.24.

scholarly journals Baddeleyite microtextures and U-Pb discordance: insights from the Spread Eagle Intrusive Complex and Cape St. Mary’s sills, Newfoundland, Canada

2020 ◽  
Author(s):  
Johannes E. Pohlner ◽  
Axel K. Schmitt ◽  
Kevin R. Chamberlain ◽  
Joshua H. F. L. Davies ◽  
Anne Hildenbrand ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Precision ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Relative Sensitivity ◽  
Ionization Mass Spectrometry ◽  
Ionization Mass ◽  
Intrusive Complex ◽  
Weighted Mean ◽  
Additional Reference

Abstract. Baddeleyite (ZrO2) is widely used in U-Pb geochronology, but different patterns of discordance often hamper accurate age interpretations. This is also the case for baddeleyite from the Spread Eagle Intrusive Complex (SEIC) and Cape St. Mary’s sills (CSMS) from Newfoundland, which we investigated combining high precision and high spatial resolution methods. Literature data and our own observations suggest that at least seven different types of baddeleyite–zircon intergrowths can be distinguished in nature, among which we describe xenocrystic zircon inclusions in baddeleyite for the first time. Baddeleyite 207Pb/206Pb dates from secondary ionization mass spectrometry (SIMS) and isotope dilution thermal ionization mass spectrometry (ID-TIMS) are in good agreement with each other and with stratigraphic data, but some SIMS sessions of grain mounts show reverse discordance. This suggests that matrix differences between references and unknowns biased the U-Pb relative sensitivity calibration, possibly due to crystal orientation effects, or due to alteration of the baddeleyite crystals, which is indicated by unusually high common Pb contents. ID-TIMS data for SEIC and CSMS single baddeleyite crystals reveal normal discordance as linear arrays with decreasing 206Pb/238U dates, indicating that their discordance is dominated by recent Pb loss due to fast pathway or volume diffusion. Hence, 207Pb/206Pb dates are more reliable than 206Pb/238U dates even for Phanerozoic baddeleyite. Negative lower intercepts of baddeleyite discordias and direct correlations between ID-TIMS 207Pb/206Pb dates and degree of discordance indicate preferential 206Pb loss, possibly due to 222Rn mobilization. In such cases, the most reliable crystallization ages are concordia upper intercept dates or weighted means of the least discordant 207Pb/206Pb dates. We regard the best estimates of the intrusion ages to be 498.7 ± 4.5 Ma (2σ; ID-TIMS upper intercept date for one SEIC dike) and 439.4 ± 0.8 Ma (ID-TIMS weighted mean 207Pb/206Pb date for one sill of CSMS). Sample SL18 of the Freetown Layered Complex, Sierra Leone (associated with the Central Atlantic Magmatic Province) was investigated as an additional reference. For SL18, we report a revised 201.07 ± 0.64 Ma intrusion age, based on a weighted mean 207Pb/206Pb date of previous and new baddeleyite ID-TIMS data, agreeing well with corresponding SIMS data. Increasing discordance with decreasing crystal size in SL18 indicates that Pb loss affected baddeleyite rims more strongly than cores. Employment of SIMS or mechanical abrasion prior to ID-TIMS analysis may therefore produce more concordant baddeleyite data. We emphasize that the combination of high precision and high spatial resolution dating, along with detailed microscale imaging of baddeleyite, is powerful for extracting reliable age information from baddeleyite from rocks with a complex post-magmatic evolution.

An Integrated Circularly Polarized Transmitter Active Phased-Array Antenna for Emerging Ka-Band Satellite Mobile Terminals

2019 ◽  
Vol 67 (8) ◽  
pp. 5344-5352 ◽  
Author(s):  
Hussam Al-Saedi ◽  
Wael M. Abdel-Wahab ◽  
S. Mohsen Raeis-Zadeh ◽  
Ehsan Haj Mirza Alian ◽  
Ardeshir Palizban ◽  
...  
Keyword(s):  
Phased Array ◽  
Array Antenna ◽  
Mobile Terminals ◽  
Phased Array Antenna ◽  
Ka Band ◽  
Circularly Polarized

scholarly journals Prediction of Sea Surface Temperature in the China Seas Based on Long Short-Term Memory Neural Networks

2020 ◽  
Vol 12 (17) ◽  
pp. 2697
Author(s):  
Li Wei ◽  
Lei Guan ◽  
Liqin Qu ◽  
Dongsheng Guo
Keyword(s):  
Spatial Resolution ◽  
Lead Time ◽  
Short Term Memory ◽  
High Spatial Resolution ◽  
Sea Surface ◽  
China Seas ◽  
Short Term ◽  
Long Short Term Memory ◽  
The China Seas

Sea surface temperature (SST) in the China Seas has shown an enhanced response in the accelerated global warming period and the hiatus period, causing local climate changes and affecting the health of coastal marine ecological systems. Therefore, SST distribution prediction in this area, especially seasonal and yearly predictions, could provide information to help understand and assess the future consequences of SST changes. The past few years have witnessed the applications and achievements of neural network technology in SST prediction. Due to the diversity of SST features in the China Seas, long-term and high-spatial-resolution prediction remains a crucial challenge. In this study, we adopted long short-term memory (LSTM)-based deep neural networks for 12-month lead time SST prediction from 2015 to 2018 at a 0.05° spatial resolution. Considering the sub-regional differences in the SST features of the study area, we applied self-organizing feature maps (SOM) to classify the SST data first, and then used the classification results as additional inputs for model training and validation. We selected nine models differing in structure and initial parameters for ensemble to overcome the high variance in the output. The statistics of four years’ SST difference between the predicted SST and Operational SST and Ice Analysis (OSTIA) data shows the average root mean square error (RMSE) is 0.5 °C for a one-month lead time and is 0.66 °C for a 12-month lead time. The southeast of the study area shows the highest predictable accuracy, with an RMSE less than 0.4 °C for a 12-month prediction lead time. The results indicate that our model is feasible and provides accurate long-term and high-spatial-resolution SST prediction. The experiments prove that introducing appropriate class labels as auxiliary information can improve the prediction accuracy, and integrating models with different structures and parameters can increase the stability of the prediction results.

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