Detecting Targets above the Earth's Surface Using GNSS-R Delay Doppler Maps: Results from TDS-1

: Global Navigation Satellite System (GNSS) reflected signals can be used to remotely sense the Earth’s surface, known as GNSS reflectometry (GNSS-R). The GNSS-R technique has been applied to numerous areas, such as the retrieval of wind speed, and the detection of Earth surface objects. This work proposes a new application of GNSS-R, namely to detect objects above the Earth’s surface, such as low Earth orbit (LEO) satellites. To discuss its feasibility, 14 delay Doppler maps (DDMs) are first presented which contain unusually bright reflected signals as delays shorter than the specular reflection point over the Earth’s surface. Then, seven possible causes of these anomalies are analysed, reaching the conclusion that the anomalies are likely due to the signals being reflected from objects above the Earth’s surface. Next, the positions of the objects are calculated using the delay and Doppler information, and an appropriate geometry assumption. After that, suspect satellite objects are searched in the satellite database from Union of Concerned Scientists (UCS). Finally, three objects have been found to match the delay and Doppler conditions. In the absence of other reasons for these anomalies, GNSS-R could potentially be used to detect some objects above the Earth’s surface.Peer ReviewedPostprint (published version

Analyzing Anomalous Artefacts in TDS-1 Delay Doppler Maps

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Global Navigation Satellite System Reflectometry (GNSS-R) uses the GNSS reflected signals to study parameters of the Earth's surface such as ocean surface height, wind speed, soil moisture, sea surface target detection. In this paper fourteen DDMs (Delay Doppler Maps) of TechDemoSat-1 (TDS-1) containing anomalous artefacts are presented and analyzed. Anomalous artefacts are not caused by the reflection from Earth surface targets, occultation, nor the leakages of direct signals, but likely - according to their delays- from reflection of targets above the Earth's surface (either airborne or spaceborne).Postprint (author's final draft

Wind direction signatures in GNSS-R observables from space

Peer ReviewedPostprint (published version

Feasibility of GNSS-R ice sheet altimetry in Greenland using TDS-1

Radar altimetry provides valuable measurements to characterize the state and the evolution of the ice sheet cover of Antartica and Greenland. Global Navigation Satellite System Reflectometry (GNSS-R) has the potential to complement the dedicated radar altimeters, increasing the temporal and spatial resolution of the measurements. Here we perform a study of the Greenland ice sheet using data obtained by the GNSS-R instrument aboard the British TechDemoSat-1 (TDS-1) satellite mission. TDS-1 was primarily designed to provide sea state information such as sea surface roughness or wind, but not altimetric products. The data have been analyzed with altimetric methodologies, already tested in aircraft based experiments, to extract signal delay observables to be used to infer properties of the Greenland ice sheet cover. The penetration depth of the GNSS signals into ice has also been considered. The large scale topographic signal obtained is consistent with the one obtained with ICEsat GLAS sensor, with differences likely to be related to L-band signal penetration into the ice and the along-track variations in structure and morphology of the firn and ice volumes The main conclusion derived from this work is that GNSS-R also provides potentially valuable measurements of the ice sheet cover. Thus, this methodology has the potential to complement our understanding of the ice firn and its evolution.Peer ReviewedPostprint (published version

Improved GNSS-R bi-static altimetry and independent DEMs of Greenland and Antarctica from TechDemoSat-1

Improved Digital Elevation Models (DEMs) of the Antarctic and Greenland Ice Sheets are presented, derived from Global Navigation Satellite Systems-Reflectometry (GNSS-R). This builds on a previous study (Cartwright et al., 2018) using GNSS-R to derive an Antarctic DEM but uses improved processing and an additional 13 months of measurements, totalling 46 months of data from the UK TechDemoSat-1 satellite. A median bias of under 10 m and root-mean-square (RMS) errors of under 53 m for the Antarctic and 166 m for Greenland are obtained, as compared to existing DEMs. The results represent, compared to the earlier study, a halving of the median bias to 9 m, an improvement in coverage of 18 %, and a four times higher spatial resolution (now gridded at 25 km). In addition, these are the first published satellite altimetry measurements of the region surrounding the South Pole. Comparisons south of 88° S yield RMS errors of less than 33 m when compared to NASA’s Operation IceBridge measurements. Differences between DEMs are explored and the future potential for ice sheet monitoring by this technique is noted

Spaceborne GNSS-Reflectometry for ocean winds: First results from the UK TechDemoSat-1 mission

First results are presented for ocean surface wind speed retrieval from reflected GPS signals measured by the Low-Earth-Orbiting UK TechDemoSat-1 satellite (TDS-1). Launched in July 2014, TDS-1 provides the first new spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) data since the pioneering UK-Disaster Monitoring Mission experiment in 2003. Examples of onboard-processed delay Doppler Maps reveal excellent data quality for winds up to 27.9 m/s. Collocated ASCAT scatterometer winds are used to develop and evaluate a wind speed algorithm based on Signal-to-Noise ratio (SNR) and the Bistatic Radar Equation. For SNR greater than 3 dB, wind speed is retrieved without bias and a precision around 2.2 m/s between 3–18 m/s even withoutcalibration. Exploiting lower SNR signals however requires good knowledge of the antenna beam, platform attitude and instrument gain setting. This study demonstrates the capabilities of low-cost, low-mass, low-power GNSS-R receivers ahead of their launch on the NASA CYGNSS constellation in 2016

First assessment of geophysical sensitivities from spaceborne Galileo and BeiDou GNSS-Reflectometry data collected by the UK TechDemoSat-1 Mission

The UK’s TechDemoSat-1 (TDS-1), launched 2014, has demonstrated the use of global positioning system (GPS) signals for monitoring ocean winds and sea ice. Here it is shown, for the first time, that Galileo and BeiDou signals detected by TDS-1 show similar promise. TDS-1 made seven raw data collections, recovering returns from Galileo and BeiDou, between November 2015 and March 2019. The retrieved open ocean delay Doppler maps (DDMs) are similar to those from GPS. Over sea ice, the Galileo DDMs show a distinctive triple peak. Analysis, adapted from that for GPS DDMs, gives Galileo’s signal-to-noise ratio (SNR), which is found to be inversely sensitive to wind speed, as for GPS. A Galileo track transiting from open ocean to sea ice shows a strong instantaneous SNR response. These results demonstrate the potential of future spaceborne constellations of GNSS-R (global navigation satellite system–reflectometry) instruments for exploiting signals from multiple systems: GPS, Galileo, and BeiDou

Sea Ice Detection Based on Differential Delay-Doppler Maps from UK TechDemoSat-1

Global Navigation Satellite System (GNSS) signals can be exploited to remotely sense atmosphere and land and ocean surface to retrieve a range of geophysical parameters. This paper proposes two new methods, termed as power-summation of differential Delay-Doppler Maps (PS-D) and pixel-number of differential Delay-Doppler Maps (PN-D), to distinguish between sea ice and sea water using differential Delay-Doppler Maps (dDDMs). PS-D and PN-D make use of power-summation and pixel-number of dDDMs, respectively, to measure the degree of difference between two DDMs so as to determine the transition state (water-water, water-ice, ice-ice and ice-water) and hence ice and water are detected. Moreover, an adaptive incoherent averaging of DDMs is employed to improve the computational efficiency. A large number of DDMs recorded by UK TechDemoSat-1 (TDS-1) over the Arctic region are used to test the proposed sea ice detection methods. Through evaluating against ground-truth measurements from the Ocean Sea Ice SAF, the proposed PS-D and PN-D methods achieve a probability of detection of 99.72% and 99.69% respectively, while the probability of false detection is 0.28% and 0.31% respectively

Improved GNSS-R bi-static altimetry and independent digital elevation models of Greenland and Antarctica from TechDemoSat-1

Improved digital elevation models (DEMs) of the Antarctic and Greenland ice sheets are presented, which have been derived from Global Navigation Satellite Systems-Reflectometry (GNSS-R). This builds on a previous study (Cartwright et al., 2018) using GNSS-R to derive an Antarctic DEM but uses improved processing and an additional 13 months of measurements, totalling 46 months of data from the UK TechDemoSat-1 satellite. A median bias of under 10 m and root-mean-square errors (RMSEs) of under 53 m for the Antarctic and 166 m for Greenland are obtained, as compared to existing DEMs. The results represent, compared to the earlier study, a halving of the median bias to 9 m, an improvement in coverage of 18 %, and a 4 times higher spatial resolution (now gridded at 25 km). In addition, these are the first published satellite altimetry measurements of the region surrounding the South Pole. Comparisons south of 88∘ S yield RMSEs of less than 33 m when compared to NASA's Operation IceBridge measurements. Differences between DEMs are explored, the limitations of the technique are noted, and the future potential of GNSS-R for glacial ice studies is discussed

Sensitivity of GNSS-R spaceborne observations to soil moisture and vegetation

Global navigation satellite systems-reflectometry (GNSS-R) is an emerging remote sensing technique that makes use of navigation signals as signals of opportunity in a multistatic radar configuration, with as many transmitters as navigation satellites are in view. GNSS-R sensitivity to soil moisture has already been proven from ground-based and airborne experiments, but studies using space-borne data are still preliminary due to the limited amount of data, collocation, footprint heterogeneity, etc. This study presents a sensitivity study of TechDemoSat-1 GNSS-R data to soil moisture over different types of surfaces (i.e., vegetation covers) and for a wide range of soil moisture and normalized difference vegetation index (NDVI) values. Despite the scattering in the data, which can be largely attributed to the delay-Doppler maps peak variance, the temporal and spatial (footprint size) collocation mismatch with the SMOS soil moisture, and MODIS NDVI vegetation data, and land use data, experimental results for low NDVI values show a large sensitivity to soil moisture and a relatively good Pearson correlation coefficient. As the vegetation cover increases (NDVI increases) the reflectivity, the sensitivity to soil moisture and the Pearson correlation coefficient decreases, but it is still significant.Postprint (author's final draft