Wind Speed Retrieval Algorithm for the Cyclone Global Navigation Satellite System (CYGNSS) Mission

2016 ◽  
Vol 54 (8) ◽  
pp. 4419-4432 ◽  
Author(s):  
Maria Paola Clarizia ◽  
Christopher S. Ruf
Keyword(s):  
Wind Speed ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Retrieval Algorithm ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Global Navigation Satellite

scholarly journals Rancang Bangun Alat Pendeteksi Kondisi Cuaca Kota Balikpapan Menggunakan Global Navigation Satellite System (GNSS) Wind Turbine

2019 ◽  
Vol 2 (2) ◽  
pp. 11-18
Author(s):  
Budiani Fitria Endrawati ◽  
Adhe Yusphie ◽  
Arum Prastiyo Putri ◽  
Azam Fadhil A ◽  
Mohammad Saiful R ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
East Kalimantan ◽  
Measurement Results ◽  
Global Navigation ◽  
Global Navigation Satellite ◽  
The City

Balikpapan is one of the cities in East Kalimantan with unique characteristic of the region. The characteristics of the region and the height of the area from the sea surface of the city of Balikpapan is one of the factors, therefore need to be designed a tool to detect weather especially in Balikpapan city. The device design using Global Navigation Satellite System (GNSS) Wind Turbine. The measurement results are based on temperature, humidity and wind speed. From the measurement of temperature, humidity and wind speed obtained an average of 30.97oC; 73.49% and 2.91 m/s. According to method World Meteorological Organization, temperature, humidity and wind speed data is accepted.

Progress in Time Series Soil Moisture Retrievals Using the Cyclone Global Navigation Satellite System Mission

2021 ◽  
Author(s):  
Mohammad Al-Khaldi ◽  
Joel Johnson ◽  
Scott Gleason
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Retrieval Algorithm ◽  
Navigation Satellite ◽  
Gps Satellites ◽  
Wide Range ◽  
Global Navigation ◽  
Global Navigation Satellite

<p>NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission has continued to provide measurements of land surface specular scattering since its launch in December 2016. CYGNSS’s operates in a GNSS-R configuration in which  CYGNSS satellites together with GPS satellites form a bistatic radar geometry with GPS satellites acting as transmitters and CYGNSS satellites acting as receivers. The fundamental GNSS-R measurement obtained using the CYGNSS observatories is the delay-Doppler map (DDM), from which normalized radar cross section (NRCS) estimates are derived. The sensitivity of CYGNSS measurements to a wide range of surface properties has motivated their use for soil moisture retrievals.</p><p>This presentation reports an updated analysis of soil moisture retrieval errors using a previously reported time series soil moisture retrieval algorithm that considers a  multi-year CYGNSS dataset. The presentation also reports recent progress in which further simplifications to the proposed algorithm are introduced that limit its need for ancillary soil moisture data and promote use in an operational capacity. This is accomplished, in part, through the incorporation of a recently developed global Level-1 coherence detection methodology and the use of a soil moisture climatology.</p><p>Soil moisture is sensed using a time-series retrieval in which NRCS ratios derived from CYGNSS measurements are used to form a system of equations that can be solved for a times series of surface reflectivities. While the NRCS exhibits a dependence on a wide range of properties such as soil moisture, soil composition, vegetation cover, and surface roughness, NRCS ratios in consecutive acquisitions, at sufficiently low latency, exhibit a direct proportionality to reflectivity ratios that are a function of soil permittivity and therefore soil moisture. The dependence of NRCS ratios on reflectivity facilitates a location dependent inversion of reflectivity to soil moisture through a dielectric mixing model. The use of NRCS ratios however results in N-1 equations for the N soil moistures in the time series, thereby necessitating the incorporation of additional information typically expressed in terms of maximum and/or minimum soil moisture (or reflectivity) values over the time series when solving the system. These values can be obtained either from ancillary data from other systems or from a soil moisture climatology as incorporated in this presentation.</p><p>Retrieved moisture values from the updated algorithm are compared against observed values reported by the Soil Moisture Active Passive (SMAP) mission. The findings suggest that there exists potential for using GNSS-R systems for global soil moisture retrievals with an RMS error on the order of 0.06 cm<sup>3</sup>/cm<sup>3</sup> over varied terrain. The dependence of the algorithm’s retrieval error on land cover class, soil texture, and moisture variability trends will be reported in detail in this presentation.</p>

scholarly journals OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fahad Alhomayani ◽  
Mohammad H. Mahoor
Keyword(s):  
Global Navigation Satellite System ◽  
Urban Areas ◽  
Satellite System ◽  
Reference Points ◽  
Navigation Satellite ◽  
Data Types ◽  
Entry Barrier ◽  
Promising Alternative ◽  
Global Navigation ◽  
Global Navigation Satellite

AbstractIn recent years, fingerprint-based positioning has gained researchers’ attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points’ number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

Implementation of a Dual-Frequency GLONASS and GPS L1 C/A Software Receiver

2010 ◽  
Vol 63 (2) ◽  
pp. 269-287 ◽  
Author(s):  
S. Abbasian Nik ◽  
M. G. Petovello
Keyword(s):  
Global Navigation Satellite System ◽  
Critical Role ◽  
Satellite System ◽  
Navigation Satellite ◽  
Dual Frequency ◽  
Software Receiver ◽  
The Public ◽  
Global Navigation ◽  
Global Navigation Satellite

These days, Global Navigation Satellite System (GNSS) technology plays a critical role in positioning and navigation applications. Use of GNSS is becoming more of a need to the public. Therefore, much effort is needed to make the civilian part of the system more accurate, reliable and available, especially for the safety-of-life purposes. With the recent revitalization of Russian Global Navigation Satellite System (GLONASS), with a constellation of 20 satellites in August 2009 and the promise of 24 satellites by 2010, it is worthwhile concentrating on the GLONASS system as a method of GPS augmentation to achieve more reliable and accurate navigation solutions.

scholarly journals Computation Approach for Quantitative Dielectric Constant from Time Sequential Data Observed by CYGNSS Satellites

2021 ◽  
Vol 13 (11) ◽  
pp. 2032
Author(s):  
Junchan Lee ◽  
Sunil Bisnath ◽  
Regina S.K. Lee ◽  
Narin Gavili Kilane
Keyword(s):  
Dielectric Constant ◽  
Soil Moisture ◽  
Global Navigation Satellite System ◽  
Measurement Data ◽  
Satellite System ◽  
Computation Method ◽  
Navigation Satellite ◽  
Local Soil ◽  
Global Navigation ◽  
Global Navigation Satellite

This paper describes a computation method for obtaining dielectric constant using Global Navigation Satellite System reflectometry (GNSS-R) products. Dielectric constant is a crucial component in the soil moisture retrieval process using reflected GNSS signals. The reflectivity for circular polarized signals is combined with the dielectric constant equation that is used for radiometer observations. Data from the Cyclone Global Navigation Satellite System (CYGNSS) mission, an eight-nanosatellite constellation for GNSS-R, are used for computing dielectric constant. Data from the Soil Moisture Active Passive (SMAP) mission are used to measure the soil moisture through its radiometer, and they are considered as a reference to confirm the accuracy of the new dielectric constant calculation method. The analyzed locations have been chosen that correspond to sites used for the calibration and validation of the SMAP soil moisture product using in-situ measurement data. The retrieved results, especially in the case of a specular point around Yanco, Australia, show that the estimated results track closely to the soil moisture results, and the Root Mean Square Error (RMSE) in the estimated dielectric constant is approximately 5.73. Similar results can be obtained when the specular point is located near the Texas Soil Moisture Network (TxSON), USA. These results indicate that the analysis procedure is well-defined, and it lays the foundation for obtaining quantitative soil moisture content using the GNSS reflectometry results. Future work will include applying the computation product to determine the characteristics that will allow for the separation of coherent and incoherent signals in delay Doppler maps, as well as to develop local soil moisture models.

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