UK TechDemoSat-1 Research Articles

Sea Ice Detection from GNSS-R Data Based on Local Linear Embedding

Sea ice plays a critical role in the Earth’s climate system, and its variations affect ecosystem stability. This study introduces a novel method for detecting sea ice in the Arctic Ocean using bidirectional radar reflections from the Global Navigation Satellite System (GNSS). Utilizing delay-Doppler maps (DDM) from the UK TechDemoSat-1 (TDS-1) satellite mission and surface data from the U.S. National Oceanic and Atmospheric Administration (NOAA), we employ the local linear embedding (LLE) algorithm for feature extraction. This approach notably reduces training costs and enhances real-time performance, while maintaining a high accuracy and robust noise immunity level. Focusing on the region above 70° north latitude throughout 2018, we aimed to distinguish between sea ice and seawater. The extracted DDM features via LLE are input into a support vector machine (SVM) for classification. The results indicate that our method achieves an accuracy of over 99% for selected low-noise data and a monthly average accuracy of 92.74% for data containing noise, while the CNN method has a monthly average accuracy of only 77.31% for noisy data. A comparative analysis between the LLE-SVM approach and the convolutional neural network (CNN) method demonstrated the superior anti-interference capabilities of the former. Additionally, the impact of the sea ice melting period on detection accuracy was analyzed.

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.

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

Abstract. 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.

Temporal variability of GNSS-Reflectometry ocean wind speed retrieval performance during the UK TechDemoSat-1 mission

This paper presents the temporal evolution of Global Navigation Satellite System Reflectometry (GNSS-R) ocean wind speed retrieval performance during three years of the UK TechDemoSat-1 (TDS-1) mission. TDS-1 was launched in July 2014 and provides globally distributed spaceborne GNSS-R data over a lifespan of over three years, including several months of 24/7 operations. TDS-1 wind speeds are computed using the NOC Calibrated Bistatic Radar Equation algorithm version 0.5 (C-BRE v0.5), and are evaluated against ERA5 high resolution re-analysis data over the period 2015–2018. Analyses reveal significant temporal variability in TDS-1 monthly wind speed retrieval performance over the three years, with the best performance (~2 m∙s−1) achieved in the early part of the mission (May 2015). The temporal variability of retrieval performance is found to be driven by several non-geophysical factors, including TDS-1 platform attitude uncertainty and spatial/temporal changes in GPS transmit power from certain satellites. Evidence is presented of the impact of the GPS Block IIF Flex mode on retrieved GNSS-R wind speed after January 2017, which results in significantly underestimated ocean winds over a large region covering the North Atlantic, northern Indian Ocean, the Mediterranean, the Black Sea, and the Sea of Okhotsk. These GPS transmit power changes are shown to induce large negative wind speed biases of up to 3 m∙s−1. Analyses are also presented of the sensitivity of TDS-1 wind speed retrieval to platform attitude uncertainty using statistical simulations. It is suggested that a 4° increase in attitude uncertainty can produce up to 1 m∙s−1 increase in RMSE, and that TDS-1 attitude data do not fully reflect actual platform attitude. We conclude that the lack of knowledge about the GNSS-R nadir antenna gain map and TDS-1 platform-attitude limits the ability to determine the achievable wind speed retrieval performance with GNSS-R on TDS-1. The paper provides recommendations that accurate attitude knowledge and a good characterisation of GNSS-R nadir antenna patterns should be prioritised for future GNSS-R missions.

Spaceborne GNSS-R Observation of Global Lake Level: First Results from the TechDemoSat-1 Mission

Spaceborne global navigation satellite system reflectometry (GNSS-R) data collected by the UK TechDemoSat-1 (TDS-1) satellite is applied to retrieve global lake levels for the first time. Lake levels of 351 global lakes (area greater than 500 km2 and elevation lower than 3000 m each) are estimated using TDS-1 Level 1b data over 2015–2017. Strong correlations (overall R2 greater than 0.95) are observed among lake levels derived from TDS-1 and other altimetry satellites such as CryoSat-2, Jason, and Envisat (the latter two are collected by Hydroweb), although with large root-mean-square error (RMSE) (tens of meters) mainly due to the fact that TDS-1 is not dedicated for altimetry measuring purpose. Examples of the Caspian Sea and the Poyang Lake show consistent spatial and temporal variations between TDS-1 and other data sources. The results in this paper provide supportive information for further application of GNSS-R constellations to measure altimetry of inland water bodies.

Geometric Distortion Correction of Spaceborne GNSS-R Delay-Doppler Map Using Reconstruction

For spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R), the delay difference of direct and reflected GNSS signals among successive snapshots changes rapidly because of the high dynamics of low earth orbital and GNSS satellites. This change has to be compensated to avoid the distortion of incoherently averaged delay-Doppler map (DDM). The method to refresh the correlation window on each coherent integration time period may require too many instrument resources or too much data to be uploaded from the ground station. This letter proposes a new postprocessing approach based on the motion degradation model of DDM and the reconstruction to replace real-time compensation. Raw sampled data from UK TechDemoSat-1 are used to verify the availability of proposed approach. The results show that after reconstruction for the distorted DDM, the DDM accuracies relative to that compensated in real time are significantly improved.

Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and Regional Differences and Impact of Different Spatial Scales

The potential of Global Navigation Satellite Systems-Reflectometry (GNSS-R) techniques to estimate land surface parameters such as soil moisture (SM) is experimentally studied using 2014–2017 global data from the UK TechDemoSat-1 (TDS-1) mission. The approach is based on the analysis of the sensitivity to SM of different observables extracted from the Delay Doppler Maps (DDM) computed by the Space GNSS Receiver–Remote Sensing Instrument (SGR-ReSI) instrument using the L1 (1575.42 MHz) left-hand circularly-polarized (LHCP) reflected signals emitted by the Global Positioning System (GPS) navigation satellites. The sensitivity of different GNSS-R observables to SM and its dependence on the incidence angle is analyzed. It is found that the sensitivity of the calibrated GNSS-R reflectivity to surface soil moisture is ~0.09 dB/% up to 30° incidence angle, and it decreases with increasing incidence angles, although differences are found depending on the spatial scale used for the ground-truth, and the region. The sensitivity to subsurface soil moisture has been also analyzed using a network of subsurface probes and hydrological models, apparently showing some dependence, but so far results are not conclusive.

TDS-1 GNSS Reflectometry: Development and Validation of Forward Scattering Winds

This study presents the development and a systematic evaluation study of GNSS reflectometry wind speeds. After establishing a wind speed retrieval algorithm, UK TechDemoSat-1 (TDS-1) derived winds, from May 2015 to July 2017, are compared to the Advanced Scatterometer (ASCAT). ERA-Interim wind fields of the European Centre for Medium-range Weather Forecasts (ECMWF) and in situ observation from Tropical Atmosphere Ocean buoy array in the Pacific are taken as reference. One-year averaged TDS-1 global winds demonstrate small differences with ECMWF in a majority of areas as well as discuss under- and overestimations. The pioneering TDS-1 winds demonstrate a root-mean-squared error (RMSE) and bias of 2.77 and $-$ 0.33 m/s, which are comparable to the RMSE and bias derived by ASCAT winds, as large as 2.31 and 0.25 m/s, respectively. Using buoys measurements as reference, RMSE and bias of 2.23 and $-$ 0.03 m/s for TDS-1 as well as 1.40 and $-$ 0.68 m/s for ASCAT are obtained. Utilizing rain microwave–infrared estimates of the Tropical Rainfall Measuring Mission, rain-affected observation of both ASCAT and TDS-1 are collected and evaluated. Although ASCAT winds show a significant performance degradation resulting in an RMSE and bias of 3.16 and 1.03 m/s, respectively, during rain condition, TDS-1 shows a more reliable performance with an RMSE and bias of 2.94 and $-$ 0.21 m/s, respectively, which indicates the promising capability of GNSS forward scattering for wind retrievals during rain. A decrease in TDS-1-derived bistatic radar cross sections during rain events, at weak winds, is also demonstrated.

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.

An Assessment of Non-geophysical Effects in Spaceborne GNSS Reflectometry Data From the UK TechDemoSat-1 Mission

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.

Ionospheric Effects in GNSS-Reflectometry From Space

Global navigation satellite systems-reflectometry (GNSS-R) is an emerging technique that uses navigation opportunistic signals as a multistatic radar. Most GNSS systems operate at L-band, which is affected by the ionosphere. At present, there is only a GNSS-R space-borne scatterometer on board the UK TechDemoSat-1, but in late 2016, NASA will launch the CYGNSS constellation, and in 2019, ESA will carry out the GEROS experiment on board the International Space Station. In GNSS-R, reflected signals are typically processed in open loop using a short coherent integration time (~1 ms), followed by long incoherent averaging (~1000 times, ~1 s) to increase the signal-to-noise ratio. In this study, the global ionospheric scintillation model is first used to evaluate the total electron content and the scintillation index S4. The ionospheric scintillation impact is then evaluated as a degradation of the signal-to-noise ratio, which can be used to assess the altimetry and scatterometry performance degradation in a generic GNSS-R mission. Since ionospheric scintillations are mostly produced by a layer of electron density irregularities at ~350 km height, underneath most LEO satellites, but closer to them than to the Earth's surface, intensity scintillations occur especially in the GNSS transmitter-to-ground transect, therefore, the impact is very similar in conventional and interferometric GNSS-R. Using UK TechDemoSat-1 data, signal-to-noise ratio fluctuations are computed and geo-located, finding that they occur in the open ocean along ~±20° from the geomagnetic equator where S4 exhibits a maximum, and in low wind speed regions, where reflected signals contain a non-negligible coherent component.

Spaceborne GNSS-R Minimum Variance Wind Speed Estimator

A Minimum Variance (MV) wind speed estimator for Global Navigation Satellite System-Reflectometry (GNSS-R) is presented. The MV estimator is a composite of wind estimates obtained from five different observables derived from GNSS-R Delay-Doppler Maps (DDMs). Regression-based wind retrievals are developed for each individual observable using empirical geophysical model functions that are derived from NDBC buoy wind matchups with collocated overpass measurements made by the GNSS-R sensor on the United Kingdom-Disaster Monitoring Constellation (UK-DMC) satellite. The MV estimator exploits the partial decorrelation that is present between residual errors in the five individual wind retrievals. In particular, the RMS error in the MV estimator, at 1.65 m/s, is lower than that of each of the individual retrievals. Although they are derived from the same DDM, the partial decorrelation between their retrieval errors demonstrates that there is some unique information contained in them. The MV estimator is applied here to UK-DMC data, but it can be easily adapted to retrieve wind speed for forthcoming GNSS-R missions, including the UK's TechDemoSat-1 (TDS-1) and NASA's Cyclone Global Navigation Satellite System (CYGNSS).

Application of the Medipix2 technology to space radiation dosimetry and hadron therapy beam monitoring

Abstract The Medipix2 Collaboration, based at CERN, has developed the TimePix version of the Medipix pixel readout chip, which has the ability to provide either an ADC or TDC capability separately in each of its 256 × 256 pixels. When coupled to a Si detector layer, the device is an excellent candidate for application as an active dosimeter for use in Space Radiation Environments. In order to facilitate such a development, data have been taken with Heavy Ions at the HIMAC facility in Chiba, Japan. In particular, the problem of determining the resolution of such a detector system with respect to heavy ions of differing charges and energies, but with similar dE/dx values has been explored for several ions. The ultimate problem is to parse the information in the pixel “footprint” images from the drift of the charge-cloud produced in the detector layer. In addition, with the use of convertor materials, the detector can be used as a neutron detector, and it has been used both as a charged particle and neutron detector to evaluate the detailed properties of the radiation fields produced by hadron therapy beams. The first space flight of a Medipix-based detector is currently planned for the first quarter of 2012 onboard the UK TechDemoSat-1 satellite as part of the LUCID project. The instrument to be flown is currently planned to have 5 TimePix versions of the Medipix2 detector deployed on 5 of the 6 faces of a cube with ∼3 cm on each side and enclosed by a 0.7 mm thick Al cylindrical cover. The planned orbit will have an altitude of 660 km and will be sun-synchronous with an inclination of 98°Current plans are for the instrument to be located on a vertical side of the satellite with one face upward, one downward, two opposed laterally and one facing in the forward direction with respect to the satellite’s velocity vector. As such, the instrument should be exposed to the outer belt electrons during polar passes as well as the South Atlantic Anomaly and ambient Galactic Cosmic Rays in addition to albedos from the atmosphere throughout its orbit. New versions of the basic chip design are ongoing.