Next Generation GNSS-R Instrument

Ruf, Christopher; Backhus, Roger; Butler, T. W.; Chen, Chi‐Chih; Gleason, Scott; Loria, Eric; McKague, Darren; Miller, Ryan; O’Brien, Andrew; Nieuwstadt, L. van

doi:10.1109/igarss39084.2020.9324588

Cited by 8 publications

(3 citation statements)

References 7 publications

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“…The instruments on each satellite are constrained as follows: a dual antenna configuration of either (a) the NASA CYGNSS mission antennas or (b) a larger dual antenna design for the higher altitude orbit simulations. The instruments are all capable of tracking up to 16 specular reflection measurements in parallel, based on the current estimated capability of the next generation of GNSS-R instruments [13]. The signal strength required for viable land and ocean observations is based on CYGNSS retrievals vs. range corrected gain (RCG), which considers both antenna gain and path losses for individual surface measurements [14,15].…”

Section: Constellation Design Baseline Assumptionsmentioning

confidence: 99%

“…In this analysis, the processing bandwidth of the GNSS-R instrument considers two cases: the existing on-orbit performance of the CYGNSS GNSS-R instrument which is capable of tracking 4 parallel reflections from GPS only [4], and a next Generation GNSS-R instrument (NGRx) which has shown in initial testing to be capable of tracking up to 16 parallel GNSS reflections from both GPS and Galileo [13]. It is possible that at some point in the future instruments will be capable of tracking more parallel reflections.…”

Section: Gnss-r Instrument Dependenciesmentioning

confidence: 99%

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Spatial and Temporal Sampling Properties of a Large GNSS-R Satellite Constellation

Winkelried

Ruf

Gleason³

2023

Remote Sensing

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Using large constellations of smallsats, mission designers can improve sampling density and coverage. We develop performance metrics that characterize key sampling properties for applications in numerical weather prediction and optimize orbit design parameters of the constellation with respect to those metrics. Orbits are defined by a set of Keplerian elements, and the relationship between those elements and the spatial and temporal coverage metrics are examined in order to maximize global and zonal (latitude-dependent) coverage. Additional optimization is performed by dividing a constellation into multiple orbit planes. An iterative method can be applied to this design process to compare the performance of current and previous designs. The main objective of this work is the design of optimized configurations of satellites in low Earth orbiting constellations to maximize the spatial and temporal sampling and coverage provided by its sensors. The key innovations developed are a new cost function which measures the temporal sampling properties of a satellite constellation, and the use of it together with existing cost functions for spatial sampling to design satellite constellations that optimize performance with respect to both performance metrics.

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Section: Constellation Design Baseline Assumptionsmentioning

confidence: 99%

Section: Gnss-r Instrument Dependenciesmentioning

confidence: 99%

Spatial and Temporal Sampling Properties of a Large GNSS-R Satellite Constellation

Winkelried

Ruf

Gleason³

2023

Remote Sensing

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“…New potential cal/val sites have been identified in the USA (Walnut Glutch, AZ, White Sands, NM) and in New Zealand. New Zealand cal/val sites are particularly of interest because the next generation GNSS-R receiver [58] is going to be installed on a regional Air New Zealand commercial aircraft to complement CYGNSS data, and to test this new receiver in preparation of a potential CYGNSS follow-on mission. An extensive analysis of the coverage provided by one Air New Zealand commercial aircraft was performed to identify the best cal/val site locations for SMC and wetlands studies.…”

Section: Land Surfacesmentioning

confidence: 99%

The CYGNSS Mission: On-Going Science Team Investigations

et al. 2021

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In 2012, the National Aeronautics and Space Administration (NASA) selected the CYclone Global Navigation Satellite System (CYGNSS) mission coordinated by the University of Michigan (UM) as a low-cost and high-science Earth Venture Mission. The CYGNSS mission was originally proposed for ocean surface wind speed estimation over Tropical Cyclones (TCs) using Earth-reflected Global Positioning System (GPS) signals, as signals of opportunity. The orbital configuration of each CYGNSS satellite is a circular Low Earth Orbit (LEO) with an altitude ~520 km and an inclination angle of ~35°. Each single Delay Doppler Mapping Instrument (DDMI) aboard the eight CYGNSS microsatellites collects forward scattered signals along four specular directions (incidence angle of the incident wave equals incidence angle of the reflected wave) corresponding to four different transmitting GPS spacecrafts, simultaneously. As such, CYGNSS allows one to sample the Earth’s surface along 32 tracks simultaneously, within a wide range of the satellites’ elevation angles over tropical latitudes. Following the Earth Science Division 2020 Senior Review, NASA announced recently it is extending the CYGNSS mission through 30 September 2023. The extended CYGNSS mission phase is focused on both ocean and land surface scientific investigations. In addition to ocean surface wind speed estimation, CYGNSS has also shown a significant ability to retrieve several geophysical parameters over land surfaces, such as Soil Moisture Content (SMC), Above Ground Biomass (AGB), and surface water extent. The on-going science team investigations are presented in this article.

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