A Real-Time On-Orbit Signal Tracking Algorithm for GNSS Surface Observations

Gleason, Scott

doi:10.3390/rs11161858

Cited by 9 publications

(12 citation statements)

References 19 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is worth noting that the specular point prediction algorithm applied in TDS-1 and CYGNSS is called the quasi-spherical Earth (QSE) approach [21], and it brings about a three-kilometer-level position error [22], which may cause trouble in DDM data processing and blur the boundary of the land-sea interface. Another conventional specular point prediction method named the minimum path length (MPL) [23,24], however, has a huge computation burden, and its accuracy varies with latitude.…”

Section: Gnss Ro Modulementioning

confidence: 99%

An Innovative Signal Processing Scheme for Spaceborne Integrated GNSS Remote Sensors

et al. 2023

View full text Add to dashboard Cite

The vigorous development of the global navigation satellite system (GNSS) has led to a boom in GNSS radio occultation (GNSS RO) and GNSS reflectometry (GNSS-R) techniques. Consequently, we have proposed an innovative signal processing scheme for spaceborne integrated GNSS remote sensors (SIGRS), combining a GNSS RO and a GNSS-R module. In the SIGRS, the GNSS-R module shares one precise orbit determination (POD) module with the GNSS RO module, and the GNSS-R module first achieves compatibility with GPS, BDS, and Galileo. Moreover, the programmable non-uniform delay resolution was introduced and first used by the SIGRS to generate the output DDM, which achieves a high delay resolution in the DDM central region around the specular point to improve the accuracy of basic observables but requires fewer delay bins than the conventional DDM with uniform delay resolution. The SIGRS has been successfully used to design the GNOS II onboard the Chinese FY-3E satellite, and the results of in-orbit operation validate the performance of the SIGRS, which means the SIGRS is an economically and technically efficient design and has become the first successful signal processing scheme for spaceborne integrated GNSS remote sensors around the world.

show abstract

Section: Gnss Ro Modulementioning

confidence: 99%

An Innovative Signal Processing Scheme for Spaceborne Integrated GNSS Remote Sensors

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The overall smoothness and uniformity of the ocean allows for the identification of a single specular reflection point at the minimum path difference between the transmitter, surface and receiver using a WGS84 ellipsoidal representation of the Earth, corrected for the mean sea surface height [17]. This technique often works well for flat land surfaces whose heights are not far from the WGS84 approximation [18].…”

Section: Surface Criteria For Forward Reflectionmentioning

confidence: 99%

“…where S W84 lat ,lon is a vector from the Earth center to the WGS84 ellipsoid position at an offset latitude (lat ) and longitude (lon ) [17], and ∆H is the DEM height above the WGS84 ellipsoid at the offset latitude and longitude. The local surface delay difference map (δτ) is produced using Equation (4) for a grid extending 100 km in all compass directions from the center reference in steps of 1 km.…”

Section: Local Surface Delay Calculationmentioning

confidence: 99%

“…In addition to the fundamental differences in surface scattering mechanisms, the geolocation of the dominant scattering region on the Earth's surface is complicated by large scale variations in land surface topography. The existing CYGNSS ocean geolocation calculation [17] uses the WGS84 ellipsoid to define the Earth's surface with a small correction for the mean sea surface height. The geolocation of land reflections requires additional consideration of local terrain variations, which can significantly shift the dominant scattering region.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Geolocation, Calibration and Surface Resolution of CYGNSS GNSS-R Land Observations

et al. 2020

Self Cite

View full text Add to dashboard Cite

This paper presents the processing algorithms for geolocating and calibration of the Cyclone Global Navigation Satellite System (CYGNSS) level 1 land data products, as well as analysis of the spatial resolution of Global Navigation Satellite System Reflectometry (GNSS-R) coherent reflections. Accurate and robust geolocation and calibration of GNSS-R land observations are necessary first steps that enable subsequent geophysical parameter retrievals. The geolocation algorithm starts with an initial specular point location on the Earth’s surface, predicted by modeling the Earth as a smooth ellipsoid (the WGS84 representation) and using the known transmitting and receiving satellite locations. Information on terrain topography is then compiled from the Shuttle Radar Topography Mission (SRTM) generated Digital Elevation Map (DEM) to generate a grid of local surface points surrounding the initial specular point location. The delay and Doppler values for each point in the local grid are computed with respect to the empirically observed location of the Delay Doppler Map (DDM) signal peak. This is combined with local incident and reflection angles across the surface using SRTM estimated terrain heights. The final geolocation confidence is estimated by assessing the agreement of the three geolocation criteria at the estimated surface specular point on the local grid, including: the delay and Doppler values are in agreement with the CYGNSS observed signal peak and the incident and reflection angles are suitable for specular reflection. The resulting geolocation algorithm is first demonstrated using an example GNSS-R reflection track that passes over a variety of terrain conditions. It is then analyzed using a larger set of CYGNSS data to obtain an assessment of geolocation confidence over a wide range of land surface conditions. Following, an algorithm for calibrating land reflected signals is presented that considers the possibility of both coherent and incoherent scattering from land surfaces. Methods for computing both the bistatic radar cross section (BRCS, for incoherent returns) and the surface reflectivity (for coherent returns) are presented. a flag for classifying returns as coherent or incoherent developed in a related paper is recommended for use in selecting whether the BRCS or reflectivity should be used in further analyses for a specific DDM. Finally, a study of the achievable surface feature detection resolution when coherent reflections occur is performed by examining a series of CYGNSS coherent reflections across an example river. Ancillary information on river widths is compared to the observed CYGNSS coherent observations to evaluate the achievable surface feature detection resolution as a function of the DDM non-coherent integration interval.

show abstract

“…This paper presents an algorithm for predicting GNSS-R reflection points in the presence of topography, which has been specifically designed for operational use onboard a small satellite. A recent paper by Gleason [11] has introduced a similar specular point prediction algorithm, developed independently, which includes the addition of a surface height term; however this is stated to only account for "low-lying land" and an operational limit is not given. In addition the algorithm in question was developed for a software receiver and although the paper mentions the possibility of its use on-board a reflectometry instrument, the actual implementation is not discussed.…”

Section: Introductionmentioning

confidence: 99%

Towards a Topographically-Accurate Reflection Point Prediction Algorithm for Operational Spaceborne GNSS Reflectometry—Development and Verification

et al. 2021

View full text Add to dashboard Cite

GNSS Reflectometry (GNSS-R), a method of remote sensing using the reflections from satellite navigation systems, was initially envisaged for ocean wind speed sensing. In recent times there has been significant interest in the use of GNSS-R for sensing land parameters such as soil moisture, which has been identified as an Essential Climate Variable (ECV). Monitoring objectives for ECVs set by the Global Climate Observing System (GCOS) organisation include a reduction in data gaps from spaceborne sources. GNSS-R can be implemented on small, relatively cheap platforms and can enable the launch of constellations, thus reducing such data gaps in these important datasets. However in order to realise operational land sensing with GNSS-R, adaptations are required to existing instrumentation. Spaceborne GNSS-R requires the reflection points to be predicted in advance, and for land sensing this means the effect of topography must be considered. This paper presents an algorithm for on-board prediction of reflection points over the land, allowing generation of DDMs on-board as well as compression and calibration. The algorithm is tested using real satellite data from TechDemoSat-1 in a software receiver with on-board constraints being considered. Three different resolutions of Digital Elevation Model are compared. The algorithm is shown to perform better against the operational requirements of sensing land parameters than existing methods and is ready to proceed to flight testing.

show abstract

A Real-Time On-Orbit Signal Tracking Algorithm for GNSS Surface Observations

Cited by 9 publications

References 19 publications

An Innovative Signal Processing Scheme for Spaceborne Integrated GNSS Remote Sensors

An Innovative Signal Processing Scheme for Spaceborne Integrated GNSS Remote Sensors

Geolocation, Calibration and Surface Resolution of CYGNSS GNSS-R Land Observations

Towards a Topographically-Accurate Reflection Point Prediction Algorithm for Operational Spaceborne GNSS Reflectometry—Development and Verification

Contact Info

Product

Resources

About