A Topographically-Accurate GNSS-R Reflection Point Predictor for on-Board Operational Processing

King, Lucinda; Unwin, Martin; Rawlinson, Jonathan; Guida, Raffaella; Underwood, Craig

doi:10.1109/igarss39084.2020.9324677

Cited by 1 publication

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References 4 publications

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“…The study presented in this paper is a continuation of work introduced at the IGARSS conference in 2020 [10].…”

Section: Introductionmentioning

confidence: 92%

“…This diagram assumes that the elevated surface is flat, which is not often the case, but is a simplification to allow the most basic form of the algorithm to be implemented (see Section 2). Reproduced from [10] with permission. 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.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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.

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“…The study presented in this paper is a continuation of work introduced at the IGARSS conference in 2020 [10].…”

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

A Topographically-Accurate GNSS-R Reflection Point Predictor for on-Board Operational Processing

Cited by 1 publication

References 4 publications

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

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

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