Search Results (24)

Sea surface height (SSH) serves as a fundamental geophysical parameter in oceanographic research. In 2023, China successfully launched the world’s first spaceborne interferometric GNSS-R (iGNSS-R) altimeter, which features dual-frequency multi-beam scanning, interferometric processing, and compatibility with three major satellite navigation systems: the BeiDou Navigation Satellite System (BDS), the Global Positioning System (GPS), and the Galileo Satellite Navigation System (GAL). This launch marked the first in-orbit validation of the iGNSS-R altimetry technology. This study provides a detailed overview of the iGNSS-R payload design and analyzes its dual-frequency delay mapping (DM) measurements. We developed a refined DM waveform-matching algorithm that precisely extracts the propagation delays between reflected and direct GNSS signals, enabling the retrieval of global sea surface height (SSH) through the interferometric altimetry model. For validation, we employed an inter-satellite crossover approach using Jason-3 and Sentinel-6 radar altimetry as references, achieving an unprecedented SSH accuracy of 17.2 cm at a 40 km resolution. This represents a breakthrough improvement over previous GNSS-R altimetry efforts. The successful demonstration of iGNSS-R technology opens up new possibilities for cost-effective, wide-swath sea level monitoring. It showcases the potential of GNSS-R technology to complement existing ocean observation systems and enhance our understanding of global sea surface dynamics. Full article

In Global Navigation Satellite System Reflectometry (GNSS-R), SNR spectrum analysis is widely used for surface altimetry inversion because of its low cost and easy operation. However, this method is somewhat limited in environmental situations with large tidal variations in sea level. In this paper, we implemented a machine learning approach to retrieve sea level height using three feature parameters of frequency, amplitude, and phase extracted by GNSS-R as inputs for the support vector regression (SVR) model, achieving better robustness in environments with large tidal variations. In this experiment, two stations, SC02 and BRST, were selected for research comparison, in which the sea surface fluctuation at the SC02 station was smaller at around 3 m while the sea surface fluctuation at the BRST station was larger at around 7 m. Global Navigation Satellite System (GNSS) observations were selected for 6 months for use to perform the assessment. The SC02 station improved 25.64% and 24.05% in the accuracy of RMSE (14.5 cm) and MAE (12.0 cm), respectively, using the SVR model compared to the conventional method (CM). In the environment with large sea level tidal fluctuations, the BRST station improved accuracy by 17.32% and 15.81% using the SVR model compared to the CM for RMSE (25.3 cm) and MAE (21.3 cm), respectively. It is shown that the SVR model is robust for sea level height retrieval with large tidal variations and that these three feature parameters, including frequency, amplitude, and phase extracted by GNSS-R, are crucial for optimizing sea surface height retrieval. Full article

Traditional spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) sea surface height (SSH) retrieval methods have the disadvantages of complicated error models, low retrieval accuracy, and difficulty using full DDM information. To compensate for these deficiencies while considering the heterogeneity of the input data, this paper proposes an end-to-end Modified Residual Multimodal Deep Learning (MRMDL) method that can utilize the entire range of DDM information. First, the MRMDL method is constructed based on the modified Residual Net (MResNet) and Multi-Hidden layer neural network (MHL-NN). The MResNet applicable to DDM structures is used to adaptively capture productive features of the full DDM and to convert the two-dimensional DDM data into one-dimensional numerical form. Then, the extracted features and auxiliary parameters are fused as the input data for MHL-NN to retrieve the SSH. Second, the reliability of the model is verified using SSH with tide-corrected DTU Sea Surface Height 18 (DTU18) and spaceborne radar altimeters (Jason3, HY-2C, HY-2B). Compared to the SSH provided by the DTU18 validation model and the spaceborne radar altimeter, the Pearson correlation coefficients (PCC) are 0.98 and 0.97, respectively. However, the CYGNSS satellite is not primarily employed for ocean altimetry, and the mean absolute differences (MAD) are 3.92 m and 4.32 m, respectively. Finally, the retrieval accuracy of the MRMDL method and the HALF retracking approach are compared and analyzed. Finally, this study also implements the HALF retracking algorithm to derive the SSH, and the results are compared with those computed by the MRMDL method. The MRMDL method is more accurate than the HALF retracking approach according to MAD, Root-Mean-Square Error (RMSE), and PCC, with an improvement of 35.21%, 17.25%, and 2.08%, respectively. The MRMDL method will contribute a new theoretical and methodological reference for future GNSS-R altimetry satellites with high spatiotemporal SSH retrieval. Full article

Ocean tidal variation is a key parameter for ensuring coastal safety, monitoring marine climate, and maintaining elevation datum. Recently, the ground-based global navigation satellite system reflectometry (GNSS-R) technique has been applied for regional tidal measurements, which is somewhat restricted in terms of temporal and spatial resolutions. A convenient method to improve temporal resolution of measurements is to combine multi-GNSS observations. This paper proposes a new sea-surface altimetry method using the posterior errors (PE) of dual-frequency carrier-phase signals derived from the ionosphere-free Precise Point Positioning (IF-PPP). Considering that the number of initial retrievals is obviously unsuitable for minute-level tidal measurements, both the time sliding window based on the Lomb–Scargle periodogram and a weighted cubic spline smoothing function are significant processing steps for estimating the reflector heights between the sea surface and antenna center. Measurements from two coastal GNSS stations with different tidal amplitudes are used to test the proposed method and compare it with the tide gauge and the signal-to-noise ratio (SNR) methods, respectively. The experimental results show that the multi-GNSS PE combination method can be used to estimate a minute-level sea level time series, and its root-mean-squared errors (RMSE) are about 12.5 cm. In terms of correlation, for all results, the corresponding coefficients exceed 0.97. Moreover, this combined PE method demonstrates a significant advantage in increasing temporal resolution, which is beneficial for application on high-frequency sea-level monitoring. Full article

The altimetry precision of conventional spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) is limited, and the error models are complicated. To compensate for the shortcomings of conventional methods, we present a new grid search multihidden layer neural network feature optimization method (GSMHLFO) for sea surface height (SSH) retrieval. Firstly, the GSMHLFO is constructed by combining the multihidden layer neural network, feature engineering, and a grid search algorithm. Moreover, the retrieval performance of the GSMHLFO and its sensitivity to various features are analyzed. By analyzing 14 feature sets with different information details, we concluded that the elevation, signal-to-noise ratio (SNR), atmospheric delay, and ocean wind speed can provide essential contributions to the SSH retrieval based on GSMHLFO. Secondly, the Technical University of Denmark 18 mean sea surface (DTU18 MSS), which is corrected by the TPXO8 global tide model, was used to verify the GSMHLFO. The number of hidden layers and neurons was optimized using the grid search algorithm. The experimental results show that the proposed GSMHLFO with four hidden layers and 200 neurons per layer has a better retrieval performance. Compared with DTU18, the mean absolute difference (MAD), the root mean square error (RMSE), and the Pearson correlation coefficient (PCC) equal 4.23 m, 5.94 m, and 0.98, respectively. The retrieval precision obtained is significantly improved compared to that reported in the literature for the TDS-1 SSH retrieval. Finally, the retrieval performance of the GSMHLFO and the traditional HALF single-point retracking method were compared. The precision of GSMHLFO is higher than that of traditional retracking method according to MAD, RMSE, and PCC, which are increased by 32.86, 25.00, and 8.99%. The GSMHLFO will provide innovative theoretical and methodological support for the high-precision SSH retrieval of GNSS-R altimetry satellites in the future. Full article

Improving the altimetric precision under the requirement of ensuring the along-track resolution is of great significance to the application of iGNSS-R satellite ocean altimetry. The results obtained by using the empirical integration time need to be improved. Optimizing the integration time can suppress the noise interference from different sources to the greatest extent, thereby improving the altimetric precision. The inverse relationship between along-track resolution and signal integration time leads to the latter not being infinite. To obtain the optimal combination of integral parameters, this study first constructs an analytical model whose precision varies with coherent integration time. Second, the model is verified using airborne experimental data. The result shows that the average deviation between the model and the measured precision is about 0.16 m. The two are consistent. Third, we apply the model to obtain the optimal coherent integration time of the airborne experimental scenario. Compared with the empirical coherent integration parameters, the measured precision is improved by about 0.1 m. Fourth, the verified model is extrapolated to different spaceborne scenarios. Then, the optimal coherent integration time and the improvement of measured precision under various conditions are estimated. It was found that the optimal coherent integration time of the spaceborne scene is shorter than that of the airborne scene. Depending on the orbital altitude and the roughness of the sea surface, its value may also vary. Moreover, the model can significantly improve the precision for low signal-to-noise ratios. The coherent integration time optimization model proposed in this paper can enhance the altimetric precision. It would provide theoretical support for the signal optimization processing and sea surface height retrieval of iGNSS-R altimetry satellites with high precision and high along-track resolution in the future. Full article

Geodetic Global Navigation Satellite System reflectometry (GNSS-R) uses ground-based signals of opportunity to retrieve sea levels at an intermediate spatial scale. Geodetic GNSS-R is based on the simultaneous reception of Line-of-Sight (LoS) and its coherent GNSS sea surface reflection (non-LOS) signals. The scope of this paper is to present geodetic GNSS-R applied to sea level altimetry. Signal-to-Noise Ratio (SNR) measurements from a Commercial Off-The-Shelf (COTS) geodetic-quality GNSS station at the Haiti Coast Guard Base in Port-au-Prince is used to retrieve sea levels in the International Terrestrial Reference Frame 2014 (ITRF2014). The GNSS-R sea levels are compared with those of the OTT Radar Level Sensor (RLS) installed vertically below the GNSS antenna. The Root-Mean-Square Error (RMSE) between the geodetic GNSS-R sea levels and OTT RLS records is 3.43 cm, with a correlation of 0.96. In addition, the complex differences between the OTT RLS records and 15-min GNSS-R sea levels using Global Positioning System (GPS) and Globalnaya Navigazionnaya Sputnikovaya Sistema (or Global Navigation Satellite System; GLONASS) signals for all the eight major tidal constituents are in mm-level agreement. Therefore, geodetic GNSS-R can be used as a complementary approach to the conventional method for sea level studies in a stable terrestrial reference frame. Full article

The elevation angle influence on coastal GNSS-R ocean code-based altimetry for GPS signals (L1 C/A and L5) and BDS B1 signals is investigated, and the corresponding correction method is presented. The study first focuses on the coastal ocean altimetry method, including the general experiment geometry and the code delay estimation using the single-point tracking algorithm. The peak power and the maximum first derivative are used as the location of the specular point. Then, the sensitivity of the height retrieved using the above coastal ocean altimetry method to elevation angle is analyzed based on the Z-V model. It can be seen that the elevation angle has a significant influence on the height retrieval, which will affect the precision of the coastal GNSS-R ocean altimetry. Finally, two correction methods, the model-driven method and the data-driven method, are proposed. The coastal altimetry experiments demonstrate that the correction methods can correct the elevation angle influence, and the data-driven method is more effective. The experimental results show that, after correcting the elevation angle influence, the code-based altimetry precision of the GPS L1 C/A signal, L5 signal, and BDS B1 signal can be up to the meter level, decimeter level (less than 4 decimeters), and meter level with respect to a reference tide gauge (TG) data set, respectively, without smoothing over time. These results provide information to guide the sea surface height retrieval using coastal GNSS-R, especially multi-satellite observation and GNSS signal with a higher chipping rate. Full article

Antenna is one of the key payloads of the GNSS-R system, and the gain is an important performance parameter. The signal-to-noise ratio (SNR) of the received signal can be improved by increasing the gain of the GNSS-R antenna, therefore the measurement accuracy is improved. However, the antenna gain and its beam width, these two performance parameters, are contradictory. If the gain of the antenna is increased, its beam width will inevitably become narrower. This narrowed beam width will affect the width of the survey strip for the GNSS-R system, which cannot meet the requirement of the high-precision and high-spatial resolution spaceborne GNSS-R sea surface altimetry in the future. In this paper, a novel dual circularly polarized phased array antenna (NDCPPA) is proposed and investigated. First, the GNSS-R satellites currently operating in orbit are all cGNSS-R systems, which use the traditional element antenna (TEA) method for measurement. The antenna used in this method is with low gain, which limits the improvement of sea surface measurement accuracy. In response to this problem, this paper establishes an NDCPPA model of iGNSS-R measurement system based on the theory of coherent signal processing on the sea surface. This model uses the high-gain scanning beam to increase the gain of the iGNSS-R antenna without affecting its coverage area, thereby improving the sea surface altimetry precision. Second, in order to verify the gain improvement effect brought by adopting the NDCPPA model, an NDCPPA model verification prototype for iGNSS-R sea surface altimetry was designed and fabricated, and then measured in a microwave anechoic chamber. The measurement results show that, compared with the TEA method, the antenna gain of our proposed verification prototype is enhanced by 9.5 dB. And the measured and designed value of the gain of the verification prototype matches well. Third, based on the GPS L1 signal, the NDCPPA model is used to analyze the effect of improving the precision of sea surface altimetry. Compared with the TEA method, the proposed model can increase the altimetric precision of the nadir point from 7.27 m to 0.21 m, which effectively improves the performance of the iGNSS-R altimetry. The NDCPPA model proposed in this article can provide the theoretical method basis and the crucial technical support for the future high-precision and high-spatial-resolution GNSS-R sea surface altimetry verification satellite. Full article

High temporal and spatial resolutions are the key advantages of the global navigation satellites system-reflectometry (GNSS-R) technique, while low precision and instabilities constrain its development. Compared with conventional Ku/C band nadir-looking radar altimetry, the precision of GNSS-R code-level altimetry is restricted by the smaller bandwidth and the lower transmitted power of the signals. Fortunately, modernized GNSS broadcast new open-available ranging codes with wider bandwidth. The Chinese BDS-3 system was built on 31 July 2020; its inclined geostationary orbit and medium circular orbit satellites provide B1C and B2a public navigation service signals in the two frequency bands of B1 and B2. In order to investigate their performance on GNSS-R code-level altimetry, a coastal experiment was conducted on 5 November 2020 at a trestle of Weihai in the Shandong province of China. The raw intermediate frequency data with a 62 MHz sampling rate were collected and post-processed to solve the sea surface height every second continuously for over eight hours. The precisions were evaluated using the measurements from a 26 GHz radar altimeter mounted on the same trestle near our GNSS-R setup. The results show that a centimeter-level accuracy of GNSS-R altimetry—based on B1C code after the application of the moving average—can be achieved, while for B2a code, the accuracy is about 10 to 20 cm. Full article

Several methods have been developed to provide polar maps of sea ice thickness (SIT) from L-band brightness temperature (T${}_B$) and altimetry data. Current process-based inversion methods to yield SIT fail to address the complex surface characteristics because sea ice is subject to strong seasonal dynamics and ice-physical properties are often non-linearly related. Neural networks can be trained to find hidden links among large datasets and often perform better on convoluted problems for which traditional approaches miss out important relationships between the observations. The FSSCat mission launched on 3 September 2020, carries the Flexible Microwave Payload-2 (FMPL-2), which contains the first Reflected Global Navigation Satellite System (GNSS-R) and L-band radiometer on board a CubeSat—designed to provide T${}_B$ data on global coverage for soil moisture retrieval, and sea ice applications. This work investigates a predictive regression neural network approach with the goal to infer SIT using FMPL-2 T${}_B$ and ancillary data (sea ice concentration, surface temperature, and sea ice freeboard). Two models—covering thin ice up to 0.6 m and full-range thickness—were separately trained on Arctic data in a two-month period from mid-October to the beginning of December 2020, while using ground truth data derived from the Soil Moisture and Ocean Salinity (SMOS) and Cryosat-2 missions. The thin ice and the full-range models resulted in a mean absolute error of 6.5 cm and 23 cm, respectively. Both of the models allowed for one to produce weekly composites of Arctic maps, and monthly composites of Antarctic SIT were predicted based on the Arctic full-range model. This work presents the first results of the FSSCat mission over the polar regions. It reveals the benefits of neural networks for sea ice retrievals and demonstrates that moderate-cost CubeSat missions can provide valuable data for applications in Earth observation. Full article

Global Navigation Satellite System Reflectometry (GNSS-R) technology is a new and promising remote sensing technology, especially satellite-based GNSS-R remote sensing, which has broad application prospects. In this work, the ionospheric impacts on space-borne GNSS-R sea surface altimetry were investigated. An analysis of optimal values for spatial filtering to remove ionospheric delays in space-borne GNSS-R altimetry was conducted. Considering that there are few satellite-borne GNSS-R orbit observations to date, simulated high-resolution space-borne GNSS-R orbital data were used for a comprehensive global and applicable study. The curves of absolute bias in relation to the bilateral filtering points were verified to achieve the minimum absolute bias. The optimal filtering points were evaluated in both statistical probability density and quantile analysis to show the reliability of the selected values. The proposed studies are helpful and valuable for the future implementation of high-accuracy space-borne GNSS-R sea surface altimetry. Full article

Mean sea surface height (MSSH) is an important parameter, which plays an important role in the analysis of the geoid gap and the prediction of ocean dynamics. Traditional measurement methods, such as the buoy and ship survey, have a small cover area, sparse data, and high cost. Recently, the Global Navigation Satellite System-Reflectometry (GNSS-R) and the spaceborne Cyclone Global Navigation Satellite System (CYGNSS) mission, which were launched on 15 December 2016, have provided a new opportunity to estimate MSSH with all-weather, global coverage, high spatial-temporal resolution, rich signal sources, and strong concealability. In this paper, the global MSSH was estimated by using the relationship between the waveform characteristics of the delay waveform (DM) obtained by the delay Doppler map (DDM) of CYGNSS data, which was validated by satellite altimetry. Compared with the altimetry CNES_CLS2015 product provided by AVISO, the mean absolute error was 1.33 m, the root mean square error was 2.26 m, and the correlation coefficient was 0.97. Compared with the sea surface height model DTU10, the mean absolute error was 1.20 m, the root mean square error was 2.15 m, and the correlation coefficient was 0.97. Furthermore, the sea surface height obtained from CYGNSS was consistent with Jason-2′s results by the average absolute error of 2.63 m, a root mean square error ( $\mathrm{RMSE}$ ) of 3.56 m and, a correlation coefficient ( $R$ ) of 0.95. Full article

High spatial resolution Global Navigation Satellite System-Reflectometry (GNSS-R) sea surface altimetry is of great significance for extracting precise information from sea surface topography. The nadir antenna is one of the key payloads for the GNSS-R altimetry satellite to capture and track the sea surface GNSS reflected signal. The observation capability of the nadir antenna directly determines the number of received reflected signals, which, in turn, affects the spatial resolution of the GNSS-R altimetry. The parameters affecting the ability of the nadir antenna to receive the reflected signal mainly include antenna gain, half-power beam width (HPBW), and pointing angle. Thus far, there are rarely studies on the observation capability of GNSS-R satellite nadir antenna. The design of operational satellite antenna does not fully combine the above three parameters to optimize the design of GNSS-R nadir antenna. Therefore, it is necessary to establish a GNSS-R spaceborne nadir antenna observation capability optimization method. This is the key to improving the number of sea surface reflected signals received by the GNSS-R altimeter satellites, thereby increasing the spatial resolution of the altimetry. This paper has carried out the following research on this. Firstly, based on the GNSS-R geometric relationship and signal processing theory, the nadir antenna signal-to-noise ratio model (NASNRM) with the gain and the elevation angle at the specular point (SP) as the main parameters is established. The accuracy of the model was verified using TechDemoSat-1 (TDS-1) observations. Secondly, based on the theory of electromagnetic scattering, considering the influence of HPBW and pointing angle on the antenna footprint size, a specular point filtering algorithm (SPFA) is proposed. Combined with the results obtained by NASNRM, the number of available specular points (SPs) is counted. The results show that as the antenna gain and the nadir-pointing angle increase, the number of SPs can reach a peak and then gradually decrease. Thirdly, combined with NASNRM and SPSA, a nadir antenna observation capability optimization method (NAOCOM) is proposed. The nadir antenna observation capability is characterized through the reflected signal utilization, and the results obtained by the method are used to optimize the combination of nadir antenna parameters. The research shows that when the orbital height of the GNSS-R satellite is 635 km, the optimal combination of nadir antenna parameters is 20.94 dBi for the gain and 32.82 degrees for the nadir-pointing angle, which can increase the observation capability of the TDS-1 satellite nadir antenna by up to 5.38 times. Full article

The positioning error of the specular reflection point is the main error source of Global Navigation Satellite System Reflectometry (GNSS-R) satellite sea surface altimetry. The existing specular reflection point geometric positioning methods do not consider the static-state elevation difference of tens of meters and the decimeter-level time-varying elevation difference between the reflection reference surface and the instantaneous sea surface. The resulting positioning error restricts the GNSS-R satellite sea surface altimetry from reaching cm-level high accuracy on the reference datum. Under the premise of the basic static-state elevation positioning error correction, reducing the time-varying elevation positioning error is the key to improving positioning accuracy. In this study, based on the principle of elevation correction of GNSS-R reflection reference surface, the main parameter that determines the real-time variation of sea surface height, ocean tide, is used to correct the specular reflection point from geoid to ocean tidal surface. The positioning error caused by the time-varying elevation error of the reflection reference surface is reduced, the positioning accuracy is improved, and the improvement is quantified. According to the research results, the ocean tidal correction positioning (OTCP) method improves the positioning accuracy by 0.31 m. The positioning accuracy improvement has a good correlation with the corresponding tidal height modulo, and the improvement is 1.07 times of the tidal height modulo. In the offshore, the tidal height gradient modulo is greater than the deep sea, the gradient of the tidal positioning correction has a good response to the tidal height gradient modulo, while the sensitivity of this response decreases in the deep sea. Full article