scholarly journals Python software to transform GPS SNR wave phases to volumetric water content

GPS Solutions ◽  
2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Angel Martín ◽  
Ana Belén Anquela ◽  
Sara Ibáñez ◽  
Carlos Baixauli ◽  
Sara Blanc
Keyword(s):  
Water Content ◽  
Scientific Community ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
Volumetric Water Content ◽  
Signal To Noise ◽  
Ratio Data ◽  
Global Navigation Satellite ◽  
Main Ideas ◽  
Extract Information

AbstractThe global navigation satellite system interferometric reflectometry is often used to extract information about the environment surrounding the antenna. One of the most important applications is soil moisture monitoring. This manuscript presents the main ideas and implementation decisions needed to write the Python code to transform the derived phase of the interferometric GPS waves, obtained from signal-to-noise ratio data continuously observed during a period of several weeks (or months), to volumetric water content. The main goal of the manuscript is to share the software with the scientific community to help users in the GPS-IR computation.

scholarly journals Signal-to-Noise Ratio Analyses of Spaceborne GNSS-Reflectometry from Galileo and BeiDou Satellites

2021 ◽  
Vol 14 (1) ◽  
pp. 35
Author(s):  
Yang Nan ◽  
Shirong Ye ◽  
Jingnan Liu ◽  
Bofeng Guo ◽  
Shuangcheng Zhang ◽  
...  
Keyword(s):  
Global Navigation Satellite System ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
Integration Time ◽  
Navigation Satellite ◽  
Signal To Noise ◽  
Coherent Integration ◽  
Global Navigation ◽  
Coherent Integration Time ◽  
Global Navigation Satellite

In recent years, Global Navigation Satellite System Reflectometry (GNSS-R) technology has made considerable progress with the increasing of GNSS-R satellites in orbit, the improvements of GNSS-R data processing technology, and the expansion of its geophysical applications. Meanwhile, with the modernization and evolution of GNSS systems, more signal sources and signal modulation modes are available. The effective use of the signals at different frequencies or from new GNSS systems can improve the accuracy, reliability, and resolution of the GNSS-R data products. This paper analyses the signal-to-noise ratio (SNR) of the GNSS-R measurements from Galileo and BeiDou-3 (BDS-3) systems, which is one of the important indicators to measure the quality of GNSS-R data. The multi-GNSS (GPS, Galileo and BDS-3) complex waveform products generated from the raw intermediate frequency data from TechDemoSat-1 (TDS-1) satellite and Cyclone Global Navigation Satellite System (CYGNSS) constellation are used for such analyses. The SNR and normalized SNR (NSNR) of the reflected signals from Galileo and BDS-3 satellites are compared to these from GPS. Preliminary results show that the GNSS-R SNRs from Galileo and BDS-3 are ∼1–2 dB lower than the GNSS-R measurements from GPS, which could be due to the power of the transmitted power and the bandwidth of the receiver. In addition, the effect of coherent integration time on GNSS-R SNR is also assessed for different GNSS signals. It is shown that the SNR of the reflected signals can be improved by using longer coherent integration time (∼0.4–0.8 dB with 2 ms coherent integration and ∼0.6–1.2 dB with 4 ms coherent integration). In addition, it is also shown that the SNR can be improved more efficiently (∼0.2–0.4 dB) for reflected BDS-3 and Galileo signals than for GPS. These results can provide useful references for the design of future spaceborne GNSS-R instrument compatible with reflections from multi-GNSS constellations.

scholarly journals QUALITY ANALYSIS OF GNSS OBSERVATIONS OF REFERENCE STATIONS NETWORK WITH THE TEQC UTILITY

2020 ◽  
Vol 25 (3) ◽  
pp. 72-88
Author(s):  
Vyacheslav E. Tereshchenko ◽  
Keyword(s):  
Signal To Noise Ratio ◽  
Satellite System ◽  
Quality Analysis ◽  
Signal To Noise ◽  
International Gnss Service ◽  
Novosibirsk Region ◽  
Russian State ◽  
Noise Ratio ◽  
Gnss Measurements ◽  
Global Navigation Satellite

The measurements of Global Navigation Satellite System (GNSS) obtained from different reference stations: Novosibirsk Region reference stations network, Russian state reference stations network ‒ Fundamental Astronomical and Geodetic Networks (FAGN) and stations of International GNSS service (IGS) are checked and analyzed. The relevance of the usage of regional (commercial or industrial) reference stations in state foundation geodetic framework for formation of a unified system of coordinate-time and navigation support is shown. The article describes quality analysis results of the GNSS measurements by the main criteria: number of rejected measurements, ionospheric delay, multipath effect, signal-to-noise ratio, receiver clock slips. The main errors affecting satellite measurements are estimated. The conclusions about the possibility of including the Novosibirsk Region reference stations network into one of the levels of the state foundation geodetic framework are drawn. The comparison of quality of the GNSS measurements showed that according to all criteria of quality the GNSS measurements of the Novosibirsk Region reference stations network are not worse than GNSS measurements of FAGN. According to all criteria the GNSS measurements of the Novosibirsk Region reference stations network approximately corresponds to GNSS measurements of IGS stations, except the signal-to-noise ratio criterion.

scholarly journals Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

2018 ◽  
Vol 10 (8) ◽  
pp. 1245 ◽  
Author(s):  
Mehrez Zribi ◽  
Erwan Motte ◽  
Nicolas Baghdadi ◽  
Frédéric Baup ◽  
Sylvia Dayau ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Signal To Noise Ratio ◽  
Soil Surface ◽  
Satellite System ◽  
Area Index ◽  
Vegetation Height ◽  
Study Sites ◽  
Global Navigation Satellite ◽  
Vegetation Characteristic ◽  
Agricultural Areas

The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI’2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

scholarly journals High-rate altimetry in SNR-based GNSS-R: Proof-of-concept of a synthetic vertical array

2021 ◽  
Author(s):  
Mauricio Kenji Yamawaki ◽  
Felipe Geremia-Nievinski ◽  
João Francisco Monico
Keyword(s):  
Sea Level ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
High Rate ◽  
Proof Of Concept ◽  
Radio Waves ◽  
Vertical Array ◽  
Remote Sensing Technique ◽  
Single Antenna ◽  
Global Navigation Satellite

Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a promising remote sensing technique for coastal sea level monitoring. The GNSS-R based on signal-to-noise ratio (SNR) observations employs a single antenna and a conventional receiver. It performs best for low elevation satellites, where direct and reflected radio waves are very similar in polarization and direction of arrival. One of the disadvantages of SNR-based GNSS-R for sea level altimetry is its low temporal resolution, which is of the order of one hour for each independent satellite pass. Here we present a proof-of-concept based on a synthetic vertical array. It exploits the mechanical movement of a single antenna at high rate (about 1 Hz). SNR observations can then be fit to a known modulation, of the order of the antenna sweeping rate. We demonstrate that centimetric altimetry precision can be achieved in a 5-minute session. [©2021 IEEE]

scholarly journals Investigation of the Occurrence of Nighttime Topside Ionospheric Irregularities in Low-Latitude and Equatorial Regions Using CYGNSS Satellites

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 708 ◽  
Author(s):  
Liang Huang ◽  
Yi Liu ◽  
Qiong Tang ◽  
Guanyi Chen ◽  
Zhuangkai Wang ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Global Analysis ◽  
Satellite System ◽  
Ionospheric Irregularities ◽  
Wave Number ◽  
Significant Finding ◽  
Low Latitude ◽  
Zonal Wave Number ◽  
Global Navigation Satellite ◽  
Maximum Occurrence

By using multi-satellite observations of the L1 signal-to-noise ratio (SNR) from the Cyclone Global Navigation Satellite System (CYGNSS) taken in 2017, we present the occurrence of nighttime topside ionospheric irregularities in low-latitude and equatorial regions. The most significant finding of this study is the existence of longitudinal structures with a wavenumber 4 pattern in the topside irregularities. This suggests that lower atmospheric waves, especially a daytime diurnal eastward-propagating zonal wave number-3 nonmigrating tide (DE3), might play an important role in the generation of topside plasma bubbles during the low solar minimum. Observations of scintillation events indicate that the maximum occurrence of nighttime topside ionospheric irregularities occurs on the magnetic equator during the equinoxes. The current work, which could be regarded as an important update of the previous investigations, would be readily for the further global analysis of the topside ionospheric irregularities.

Experimental results of multipath behavior for GPS L1-L2 and Galileo E1-E5b in static and kinematic scenarios

2019 ◽  
Vol 13 (4) ◽  
pp. 279-289 ◽  
Author(s):  
Alexandra Avram ◽  
Volker Schwieger ◽  
Noha El Gemayel
Keyword(s):  
Signal To Noise Ratio ◽  
Measurement Data ◽  
Absolute Error ◽  
Autonomous Driving ◽  
Satellite System ◽  
Natural Environments ◽  
Navigation Systems ◽  
Global Navigation Satellite ◽  
The Impact ◽  
Measurement Campaigns

Abstract Current trends like Autonomous Driving (AD) increase the need for a precise, reliable, and continuous position at high velocities. In both natural and man-made environments, Global Navigation Satellite System (GNSS) signals suffer challenges such as multipath, attenuation, or loss-of-lock. As Highway Assist and Highway Pilot are AD next steps, multipath knowledge is necessary for this typical user-case and kinematic situations. This paper presents a multipath performance analysis for GPS and Galileo satellites in static, slow, and high kinematic scenarios. The data is provided from car test-drives in both controlled and unrestricted, near-natural environments. The Code-Minus-Carrier (CMC) and cycle-slip implementations are validated with measurement data from consecutive days. Multipath statistical models based on satellite elevation are evaluated for the three investigated scenarios. Static models derived from the car setup measurements for GPS L1, L2 and Galileo E1 and E5b show a good agreement with a state-of-the-art model as well as the enhanced Galileo signals performance. Slow kinematic multipath results in a controlled environment showed an improvement for both navigation systems compared to the static measurements at the same place. This result is confirmed by static and slow kinematic multipath simulations with the same GNSS receiver. Post-processing analysis on highway measurements revealed a bigger multipath bias, compared to the open-sky static and slow kinematic measurement campaigns. Although less critical as urban or rural, this indicates the presence of multipath in this kind of environment as well. The impact of different parameters, including receiver architecture and Signal-to-noise ratio (SNR) are analyzed and discussed. Differential position (DGNSS) based on code is computed for each epoch and compared against GNSS/INS integrated position for all three measurement campaigns. The most significant 3D absolute error occurs where the greatest multipath envelope is found.

scholarly journals THERMAL IR IMAGING: IMAGE QUALITY AND ORTHOPHOTO GENERATION

2018 ◽  
Vol XLII-1 ◽  
pp. 413-420 ◽  
Author(s):  
A. Sledz ◽  
J. Unger ◽  
C. Heipke
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Automatic Generation ◽  
Satellite System ◽  
Night Time ◽  
World Coordinate System ◽  
Image Capturing ◽  
Aerial Vehicle ◽  
Rgb Images ◽  
Global Navigation Satellite

<p><strong>Abstract.</strong> This paper deals with two aspects of photogrammetric processing of thermal images: image quality and 3D reconstruction quality. The first aspect of the paper relates to the influence of day light on Thermal InfraRed (TIR) images captured by an Unmanned Aerial Vehicle (UAV). Environmental factors such as ambient temperature and lack of sun light affect TIR image quality. We acquire image sequences of the same object during day and night and compare the generated orthophotos according to different metrics like contrast and signal-to-noise ratio (SNR). Our experiments show that performing TIR image acquisition during night time provides a better thermal contrast, regardless of whether we compute contrast over the whole image or over small patches. The second aspect investigated in this work is the potential of using TIR images for photogrammetric tasks such as the automatic generation of Digital Surface Models (DSM) and orthophotos. Due to the low geometrical resolution of a TIR camera and the low image quality in terms of contrast and noise compared to RGB images, the TIR DSM suffers from reconstruction errors and an orthophoto generated using the TIR DSM and TIR images is visibly influenced by those errors. We therefore include measurements of the UAVs positions during image capturing provided by a Global Navigation Satellite System (GNSS) receiver to retrieve position and orientation of TIR and RGB images in the same world coordinate system. To generate an orthophoto from TIR images, they are projected onto the DSM reconstructed from RGB images. This procedure leads to a TIR orthophoto of much higher quality in terms of geometrical correctness.</p>

scholarly journals Moving Target Detection in Multi-Static GNSS-Based Passive Radar Based on Multi-Bernoulli Filter

2020 ◽  
Vol 12 (21) ◽  
pp. 3495
Author(s):  
HongCheng Zeng ◽  
Jie Chen ◽  
PengBo Wang ◽  
Wei Liu ◽  
XinKai Zhou ◽  
...  
Keyword(s):  
Target Detection ◽  
Sequential Monte Carlo ◽  
Signal To Noise Ratio ◽  
Power Level ◽  
Estimation Method ◽  
Satellite System ◽  
Moving Target ◽  
Passive Radar ◽  
Moving Target Detection ◽  
Global Navigation Satellite

Over the past few years, the global navigation satellite system (GNSS)-based passive radar (GBPR) has attracted more and more attention and has developed very quickly. However, the low power level of GNSS signal limits its application. To enhance the ability of moving target detection, a multi-static GBPR (MsGBPR) system is considered in this paper, and a modified iterated-corrector multi-Bernoulli (ICMB) filter is also proposed. The likelihood ratio model of the MsGBPR with range-Doppler map is first presented. Then, a signal-to-noise ratio (SNR) online estimation method is proposed, which can estimate the fluctuating and unknown map SNR effectively. After that, a modified ICMB filter and its sequential Monte Carlo (SMC) implementation are proposed, which can update all measurements from multi-transmitters in the optimum order (ascending order). Moreover, based on the proposed method, a moving target detecting framework using MsGBPR data is also presented. Finally, performance of the proposed method is demonstrated by numerical simulations and preliminary experimental results, and it is shown that the position and velocity of the moving target can be estimated accurately.

Enhancing Element Identification by Expectation–Maximization Method in Atom Probe Tomography

2019 ◽  
Vol 25 (2) ◽  
pp. 367-377 ◽  
Author(s):  
Francois Vurpillot ◽  
Constantinos Hatzoglou ◽  
Bertrand Radiguet ◽  
Gerald Da Costa ◽  
Fabien Delaroche ◽  
...  
Keyword(s):  
Data Analysis ◽  
Data Visualization ◽  
Expectation Maximization ◽  
Atom Probe Tomography ◽  
Mass Spectra ◽  
Signal To Noise Ratio ◽  
Atom Probe ◽  
Decomposition Methods ◽  
Signal To Noise ◽  
Extract Information

AbstractThis paper describes an alternative way to assign elemental identity to atoms collected by atom probe tomography (APT). This method is based on Bayesian assignation of label through the expectation–maximization method (well known in data analysis). Assuming the correct shape of mass over charge peaks in mass spectra, the probability of each atom to be labeled as a given element is determined, and is used to enhance data visualization and composition mapping in APT analyses. The method is particularly efficient for small count experiments with a low signal to noise ratio, and can be used on small subsets of analyzed volumes, and is complementary to single-ion decomposition methods. Based on the selected model and experimental examples, it is shown that the method enhances our ability to observe and extract information from the raw dataset. The experimental case of the superimposition of the Si peak and N peak in a steel is presented.

Sign in / Sign up

Export Citation Format

Share Document