Abstract

An assessment of non-geophysical effects in spaceborne global navigation satellite system reflectometry (GNSS-R) data from the UK TechDemoSat-1 (TDS-1) mission is presented. TDS-1 was launched in July 2014 and provides the first new spaceborne GNSS-R data since the pioneering UK-disaster monitoring constellation experiment in 2003. Non-geophysical factors evaluated include ambient L-band noise, instrument operating mode, and platform-related parameters. The findings are particularly relevant to users of uncalibrated GNSS-R signals for the retrieval of geophysical properties of the Earth surface. Substantial attitude adjustments of the TDS-1 platform are occasionally found to occur that introduce large uncertainties in parts of the TDS-1 GNSS-R dataset, particularly for specular points located outside the main beam of the nadir antenna where even small attitude errors can lead to large inaccuracies in the geophysical inversion. Out of eclipse however, attitude adjustments typically remain smaller than 1.5°, with larger deviations of up to 10° affecting less than 5% of the overall sun-lit data. Global maps of L1 ambient noise are presented for both automatic and programmed gain modes of the receiver, revealing persistent L-band noise hotspots along the Equator that can reach up to 2.5 dB, most likely associated with surface reflection of signals from other GNSS transmitters and constellations. Sporadic high-power noise events observed in certain regions point to sources of human origin. Relevant conclusions of this study are that platform attitude knowledge is essential and that radiometric calibration of GNSS-R signals should be used whenever possible. Care should be taken when considering using noise measurements over the equatorial oceans for calibration purposes, as ambient noise and correlated noise in delay–Doppler maps both show more variation than might be expected over these regions.

Highlights

  • G LOBAL navigation satellite system reflectometry (GNSS-R) is a well-known new remote sensing technique exploiting global navigation satellite system (GNSS) signals reflected off the surface of the Earth in a forward scattered bistatic radar configuration, where the transmitter is a GNSS satellite in medium Earth orbit (MEO) and the receiver is a passive instrument on a separate platform such as a low Earth orbit satellite

  • We presented an overview of the TDS-1 GNSS-R dataset acquired to date in various instrumental modes, highlighting a number of non-geophysical factors in spaceborne GNSS-R that could impact the geophysical inversion and interpretation of GNSS-R signals typically used for the retrieval of winds and ocean roughness

  • Spaceborne GNSS-R data from the UK TDS-1 mission were examined to report on key features of the TDS-1 dataset and highlighting various non-geophysical effects in the data

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Summary

Introduction

G LOBAL navigation satellite system reflectometry (GNSS-R) is a well-known new remote sensing technique exploiting global navigation satellite system (GNSS) signals reflected off the surface of the Earth in a forward scattered bistatic radar configuration, where the transmitter is a GNSS satellite in medium Earth orbit (MEO) and the receiver is a passive instrument on a separate platform such as a low Earth orbit satellite. The use of passive receiving hardware enables the design of low mass, low-power, low-cost instruments that can be flown on constellations of small satellites [1]–[3] or as payloads of opportunity on other platforms/missions. This potential for low-cost implementation provides the option to build a comparably affordable Earth observation system characterized by sensors on multiple satellites to achieve very high spatiotemporal sampling of surface geophysical parameters such as ocean surface winds. Among its eight experimental payloads, it includes the SGR-ReSI, a low mass, low-power, low-cost GNSS reflectometry receiver developed by Surrey Satellite Technology Limited. The SGR-ReSI is a precursor of the GNSS-R receivers to be flown on the NASA CYGNSS mission due for launch in late 2016 [7]

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