scholarly journals Response to Variations in River Flowrate by a Spaceborne GNSS-R River Width Estimator

2019 ◽  
Vol 11 (20) ◽  
pp. 2450 ◽  
Author(s):  
April Warnock ◽  
Christopher Ruf
Keyword(s):  
Remote Sensing ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Radar System ◽  
Bistatic Radar ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Highly Correlated ◽  
Global Navigation Satellite

In recent years, the use of Global Navigation Satellite System-Reflectometry (GNSS-R) for remote sensing of the Earth’s surface has gained momentum as a means to exploit existing spaceborne microwave navigation systems for science-related applications. Here, we explore the potential for using measurements made by a spaceborne GNSS-R bistatic radar system (CYGNSS) during river overpasses to estimate its width, and to use that width as a proxy for river flowrate. We present a case study utilizing CYGNSS data collected in the spring of 2019 during multiple overpasses of the Pascagoula River in southern Mississippi over a range of flowrates. Our results demonstrate that a measure of river width derived from CYGNSS is highly correlated with the observed flowrates. We show that an approximately monotonic relationship exists between river flowrate and a measure of river width which we define as the associated GNSS-R width (AGW). These results suggest the potential for GNSS-R systems to be utilized as a means to estimate river flowrates and widths from space.

Aircraft positioning using GPS/GLONASS code observations

2019 ◽  
Vol 92 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Kamil Krasuski ◽  
Janusz Cwiklak ◽  
Marek Grzegorzewski
Keyword(s):  
Global Navigation Satellite System ◽  
Single Point ◽  
Satellite System ◽  
Least Square ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Protection Level ◽  
Content Type ◽  
Global Navigation ◽  
Global Navigation Satellite

Purpose This paper aims to present the problem of the integration of the global positioning system (GPS)/global navigation satellite system (GLONASS) data for the processing of aircraft position determination. Design/methodology/approach The aircraft coordinates were obtained based on GPS and GLONASS code observations for the single point positioning (SPP) method. The numerical computations were executed in the aircraft positioning software (APS) package. The mathematical scheme of equation observation of the SPP method was solved using least square estimation in stochastic processing. In the research experiment, the raw global navigation satellite system data from the Topcon HiperPro onboard receiver were applied. Findings In the paper, the mean errors of an aircraft position from APS were under 3 m. In addition, the accuracy of aircraft positioning was better than 6 m. The integrity term for horizontal protection level and vertical protection level parameters in the flight test was below 16 m. Research limitations/implications The paper presents only the application of GPS/GLONASS observations in aviation, without satellite data from other navigation systems. Practical implications The presented research method can be used in an aircraft based augmentation system in Polish aviation. Social implications The paper is addressed to persons who work in aviation and air transport. Originality/value The paper presents the SPP method as a satellite technique for the recovery of an aircraft position in an aviation test.

scholarly journals Legal Review of the Liability Framework for Remote Sensing by Looking at the Global Navigation Satellite System (GNSS)

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Simin Asadzadeh Talei ◽  
Sepideh Bouzari ◽  
Sakineh Bagheri
Keyword(s):  
Remote Sensing ◽  
Global Navigation Satellite System ◽  
Civil Liability ◽  
Satellite System ◽  
Navigation Satellite ◽  
Legal Recognition ◽  
The Subject ◽  
Global Navigation ◽  
The Law ◽  
Global Navigation Satellite

Compensation for losses in the law is certain and the civil liability system is designed to respond to this need. Nowadays, it is necessary to check compensation in different fields, and specialists in each field are seeking data to recognize liability issues and even reduce the risk of liability in their work. The legal recognition of the subject is necessary because the field of remote sensing and mapping is one of the fields with many activists and plays an important role in various aspects of the life of the community, but many people still do not have any data about their rights, and even those involved in this field as producers or consumers does not have legal data on this issue, and due to the involvement of this data in the lives of individuals and the existence of relevant cases in the judiciary. Therefore, the accurate recognition of this issue will cause questions in this field to be answered in law. And lawyers and judges can also rely on the recognition and analysis of this issue to avoid error and work more efficiently.Key words: Liability, Remote Sensing, Fault, Global Navigation Satellite System (GNSS)

scholarly journals Recent Progress on Vegetation Remote Sensing Using Spaceborne GNSS-Reflectometry

2021 ◽  
Vol 13 (21) ◽  
pp. 4244
Author(s):  
Xuerui Wu ◽  
Peng Guo ◽  
Yueqiang Sun ◽  
Hong Liang ◽  
Xinggang Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Content ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Weak Links ◽  
Navigation Satellite ◽  
Exploratory Research ◽  
Vegetation Monitoring ◽  
Global Navigation ◽  
Global Navigation Satellite

Vegetation is an important part of the terrestrial ecosystem and plays a vital role in the global carbon cycle. Traditional remote sensing methods have certain limitations in vegetation monitoring, and the development of GNSS-R (Global Navigation Satellite System-Reflectometry) technology provides a new and complimentary method. With the CYGNSS (Cyclone Global Navigation Satellite System) launch and the increased data acquisition, the use of spaceborne GNSS-R for vegetation monitoring has become a research hotspot. However, due to the complex characteristics of vegetation, its application in this field is still in the exploratory research stage. On the basis of reviewing the current research status, this paper points out the weak links of this technology in terms of polarization and observation geometry. Combined with the microwave vegetation scattering model, this paper analyzes the full polarization bistatic scattering characteristics of vegetation and points out the influence of vegetation parameters (density, water content, and vegetation diameters). The potential feasibility of polarization GNSS-R and future development trends of GNSS-R technology in quantitative retrieval (such as vegetation water content and biomass) are also discussed.

scholarly journals Semi-tightly coupled integration of multi-GNSS PPP and S-VINS for precise positioning in GNSS-challenged environments

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Xingxing Li ◽  
Xuanbin Wang ◽  
Jianchi Liao ◽  
Xin Li ◽  
Shengyu Li ◽  
...  
Keyword(s):  
Global Navigation Satellite System ◽  
Inertial Navigation ◽  
Satellite System ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Tight Coupling ◽  
Positioning Accuracy ◽  
3D Positioning ◽  
Global Navigation ◽  
Global Navigation Satellite

AbstractBecause of its high-precision, low-cost and easy-operation, Precise Point Positioning (PPP) becomes a potential and attractive positioning technique that can be applied to self-driving cars and drones. However, the reliability and availability of PPP will be significantly degraded in the extremely difficult conditions where Global Navigation Satellite System (GNSS) signals are blocked frequently. Inertial Navigation System (INS) has been integrated with GNSS to ameliorate such situations in the last decades. Recently, the Visual-Inertial Navigation Systems (VINS) with favorable complementary characteristics is demonstrated to realize a more stable and accurate local position estimation than the INS-only. Nevertheless, the system still must rely on the global positions to eliminate the accumulated errors. In this contribution, we present a semi-tight coupling framework of multi-GNSS PPP and Stereo VINS (S-VINS), which achieves the bidirectional location transfer and sharing in two separate navigation systems. In our approach, the local positions, produced by S-VINS are integrated with multi-GNSS PPP through a graph-optimization based method. Furthermore, the accurate forecast positions with S-VINS are fed back to assist PPP in GNSS-challenged environments. The statistical analysis of a GNSS outage simulation test shows that the S-VINS mode can effectively suppress the degradation of positioning accuracy compared with the INS-only mode. We also carried out a vehicle-borne experiment collecting multi-sensor data in a GNSS-challenged environment. For the complex driving environment, the PPP positioning capability is significantly improved with the aiding of S-VINS. The 3D positioning accuracy is improved by 49.0% for Global Positioning System (GPS), 40.3% for GPS + GLOANSS (Global Navigation Satellite System), 45.6% for GPS + BDS (BeiDou navigation satellite System), and 51.2% for GPS + GLONASS + BDS. On this basis, the solution with the semi-tight coupling scheme of multi-GNSS PPP/S-VINS achieves the improvements of 41.8–60.6% in 3D positioning accuracy compared with the multi-GNSS PPP/INS solutions.

scholarly journals Ionospheric Remote Sensing with GNSS

Encyclopedia ◽  
2021 ◽  
Vol 1 (4) ◽  
pp. 1246-1256
Author(s):  
YuXiang Peng ◽  
Wayne A. Scales
Keyword(s):  
Remote Sensing ◽  
Global Navigation Satellite System ◽  
Charged Particles ◽  
Satellite System ◽  
Upper Atmosphere ◽  
Pivotal Role ◽  
Navigation Satellite ◽  
Plasma Medium ◽  
Physical Processes ◽  
Global Navigation Satellite

The Global Navigation Satellite System (GNSS) plays a pivotal role in our modern positioning, navigation and timing (PNT) technologies. GNSS satellites fly at altitudes of approximately 20,000 km or higher. This altitude is above an ionized layer of the Earth’s upper atmosphere, the so called “ionosphere”. Before reaching a typical GNSS receiver on the ground, GNSS satellite signals penetrate through the Earth’s ionosphere. The ionosphere is a plasma medium consisting of free charged particles that can slow down, attenuate, refract, or scatter the GNSS signals. Ionospheric density structures (also known as irregularities) can cause GNSS signal scintillations (phase and intensity fluctuations). These ionospheric impacts on GNSS signals can be utilized to observe and study physical processes in the ionosphere and is referred to ionospheric remote sensing. This entry introduces some fundamentals of ionospheric remote sensing using GNSS.

scholarly journals Evaluation of CYGNSS Observations for Flood Detection and Mapping during Sistan and Baluchestan Torrential Rain in 2020

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2047
Author(s):  
Mahmoud Rajabi ◽  
Hossein Nahavandchi ◽  
Mostafa Hoseini
Keyword(s):  
Remote Sensing ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Management Options ◽  
Torrential Rain ◽  
Global Navigation ◽  
Flood Detection ◽  
Global Navigation Satellite ◽  
Sistan And Baluchestan

Flood detection and produced maps play essential roles in policymaking, planning, and implementing flood management options. Remote sensing is commonly accepted as a maximum cost-effective technology to obtain detailed information over large areas of lands and oceans. We used remote sensing observations from Global Navigation Satellite System-Reflectometry (GNSS-R) to study the potential of this technique for the retrieval of flood maps over the regions affected by the recent flood in the southeastern part of Iran. The evaluation was made using spaceborne GNSS-R measurements over the Sistan and Baluchestan provinces during torrential rain in January 2020. This area has been at a high risk of flood in recent years and needs to be continuously monitored by means of timely observations. The main dataset was acquired from the level-1 data product of the Cyclone Global Navigation Satellite System (CYGNSS) spaceborne mission. The mission consisted of a constellation of eight microsatellites with GNSS-R sensors onboard to receive forward-scattered GNSS signals from the ocean and land. We first focused on data preparation and eliminating the outliers. Afterward, the reflectivity of the surface was calculated using the bistatic radar equations formula. The flooded areas were then detected based on the analysis of the derived reflectivity. Images from Moderate-Resolution Imaging Spectroradiometer (MODIS) were used for evaluation of the results. The analysis estimated the inundated area of approximately 19,644 km2 (including Jaz-Murian depression) to be affected by the flood in the south and middle parts of the Sistan and Baluchestan province. Although the main mission of CYGNSS was to measure the ocean wind speed in hurricanes and tropical cyclones, we showed the capability of detecting floods in the study area. The sensitivity of the spaceborne GNSS-R observations, together with the relatively short revisit time, highlight the potential of this technique to be used in flood detection. Future GNSS-R missions capable of collecting the reflected signals from all available multi-GNSS constellations would offer even more detailed information from the flood-affected areas.

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