This study demonstrates the utility of the Global Navigation Satellite System Reflectometry (GNSS-R) method for remote sensing of ice shelf surface deformation and roughness. The phase coherence of the reflected GNSS carrier signal is related to surface deformation and roughness: smoother, less deformed areas scatter the signal more coherently. More than 900000 tracks of Spire Global Inc. grazing angle GNSS-R data collected over Antarctica between 2021 and 2023 were processed to determine signal carrier phase coherence. Results are presented in the form of coherence maps, where each measurement has a spatial resolution of approximately five kilometers, and the Ross Ice Shelf (RIS) is used as a case study for more detailed examination. Clear visual patterns in signal coherence are shown to correspond with the locations of streaklines and deformation features on the surface. A GNSS-R coherence-based roughness proxy is introduced and shown to correlate with surface roughness derived from the reference elevation model of Antarctica digital elevation model (REMA DEM). This novel application of the GNSS-R method demonstrates the exciting potential to complement existing data sources and improve understanding of ice shelf structure and evolution.

This study utilizes Global Navigation Satellite System Reflectometry (GNSS-R) to map the surface of the Ross Ice Shelf in Antarctica. Spaceborne GNSS-R is a relatively new method for cryosphere applications and utilizes reflected GNSS signals of opportunity collected on a platform in low-Earth orbit, allowing for widespread data coverage with better temporal resolution than conventional remote sensing technologies. Coherency of the reflected signal, computed using phase-based circular statistics, can be used as a proxy for surface roughness. Using 25819 Spire Global grazing angle reflectometry tracks, we generate a high-resolution map of coherency over the Ross Ice Shelf. This technique shows promise for identifying regions with similar surface characteristics and deformation history, as well as for detecting the ice shelf/sea ice border, large rifts, and flow lines.

This paper investigates using Spire’s grazing-angle GNSS-R data to detect the existence of surface water in the lower Mississippi region. The Signal-to-Noise Ratio (SNR) of the reflected L2 GPS signals acquired using the Spire Global constellation are analyzed over several tracks covering the Mississippi river, along with Normalized Difference Vegetation Index (NDVI) from Sentinel-2 Multispectral Imager (MSI) and backscattering coefficients from Sentinel-1 Synthetic Aperture Radar (SAR) C-band acquisitions. The specular points are segregated on the basis of thresholds based on the GNSS data and associated remote sensing data with correctly classifying the points over water with a true positive rate between 55-70% for L2 SNR thresholds above noise floor.

This paper describes a preliminary investigation into the relationship of Global Navigation Satellite System-Reflectometry (GNSS-R) phase-based coherency and signal-to-noise ratio (SNR) with the extent of surface water contained in the reflected the signal's spatial footprint. Our study focuses on 82 phase-based GNSS-R tracks collected by Spire Global grazing angle satellites in 2021 over Lake Okeechobee, FL. For each track, we calculate its spatial footprint (assumed equal to the First Fresnel Zone (FFZ)) and determine the amount of surface water within the FFZ using a lake mask derived from the 2021 Global Surface Water Explorer (GWSE) Seasonality product. The percentage of surface water in the signal footprint (denoted %F) is compared with the reflected signal's SNR and level of coherency, with coherency measured by the phase-rate circular length. Overall, we see a positive relationship between SNR, circular length, and %F. However, circular length appears to be a more robust indicator of water, with more consistent, high magnitudes once the scattering surface is dominantly water (>70%F). Further, circular length appears to maintain a high magnitude at different distances into Lake Okeechobee when the footprint is full of water, whereas SNR gradually decreases as the signal track approaches the center of the lake. This is most likely a result of wind roughening the lake surface farther away from the shore.

When GNSS signals reflect off of the surfaces of lakes, rivers, wetlands, and other inland water bodies, the surfaces are often sufficiently smooth to produce coherent reflections. The observable produced from coherent reflections made by GNSS Reflectometry (GNSS-R) instruments exhibits particular features with respect to diffusely scattered signals by rough land and wind-driven oceans allowing detection of such smooth bodies. Several different GNSS-R coherence detection approaches have been reported in the literature and developed among the GNSS-R community over the last several years; however, the merits of each approach are difficult to compare because they are often applied to different scenarios and quantified in different ways, independently of each other. This paper provides a unified comparison of a wide variety of different GNSS-R coherence detection approaches, which is the most extensive published to date. The approaches are applied to a common data set from the NASA CYGNSS satellites that includes both the standard Level-1 DDM science product as well as raw baseband signal recordings. Additionally, simulated observables are generated with varying coherent and non-coherent reflection components to exercise algorithms over a wide range of SNRs and relative powers. Objective measures of accuracy are used to quantify the performance of each approach in the context of relative implementation complexity. Conclusions are presented on the pros/cons of the various methods as they relate to various applications such as real-time in-orbit coherence detection or post-processing on the ground.

Spaceborne global navigation satellite system-reflectometry (GNSS-R) has the potential to provide a new data source for inland water surface observations. In this paper, we present several case studies for the Mississippi River surface gradient observations using the GNSS-R data from Spire's CubeSats. The retrieved river surface slopes are in a range from 2.2 to 16.6 cm/km, and the lower river sections tend to be more flat. Higher phase noise is observed from Spire's GNSS-R data compared previous studies using CY GNSS data. It is likely due to the Spire CubeSat antenna design and the low elevation angles of the reflection signals. A lower elevation angle corresponds to a larger footprint of up to several kilometers and thus may introduce strong multipath interference in the measurements. The presented results also confirmed the GNSS-R observation of superelevation phenomenon that was first discussed in [1]. The ionosphere effects and L2 signal's competitive contributions to the retrieval noise and ionospheric correction are also discussed.

Coherent reflections of global navigation satellite system (GNSS) signals have a measurable carrier phase, enabling higher precision for certain GNSS-based Earth remote sensing applications. In this letter, we explore the dependence of coherence on three land surface characteristics: surface water, topography, and soil moisture (SM). Carrier phase measurements are obtained by tracking raw intermediate frequency data collected by the cyclone GNSS (CYGNSS) mission. In total, several hundred data collections between 2017 and 2019 are analyzed. The phase coherence, quantified using statistics of the tracked carrier phase, is compared to the corresponding land characteristics on a per-track basis and across the entire dataset. On a per-track basis, we find that the level of coherence can often be explained by the presence of surface water, with no obvious dependence on topography or SM. However, by analyzing the entire dataset, we show that topography and SM have a weak but noticeable impact on the coherence.

This letter demonstrates the potential of estimating river surface slope using space-borne global navigation satellite system-reflectometry (GNSS-R) carrier phase measurements. A case study is presented where the slopes of several segments of the Orinoco river are retrieved based on the processing of raw intermediate-frequency (IF) data recorded by the cyclone global navigation satellite system (CYGNSS) mission. The retrieved river slopes mostly vary between 3.9 and 5.1 cm/km and are in agreement with the surveyed mean slope of 4.5 cm/km for the lower Orinoco River. The correction and calibration of several systematic errors, i.e., CYGNSS satellite orbit errors, tropospheric and ionospheric effects, and river surface reference height error, are discussed in this letter. For the Orinoco River case study, the river slope retrieval is calibrated using the reflection signal over a nearby lake to mitigate the mis-modeled and unmodeled errors. Analysis of the specular point (SP) tracks of GPS reflection signal indicates that CYGNSS has the potential to provide river slope observations for rivers that have sufficient width with high temporal and spatial resolutions.

Ionospheric total electron content (TEC) maps with high spatial and temporal resolutions are essential for depicting the state of the ionosphere and for performing ionospheric delay corrections associated with satellite navigation applications. Low Earth orbit (LEO) CubeSat-based global navigation satellite system (GNSS) reflectometry (GNSS-R) measurements provide a promising opportunity for retrieval of ionospheric TEC over sea ice and calm waters, which offers a potential new data source to fill the gaps of ground-based GNSS networks. However, the GNSS-R slant TEC (sTEC) estimations include contributions from the incident and reflection ray paths, whose ionospheric piercing points (IPPs) can be separated by hundreds of kilometers. This article presents an algorithm that integrates sTEC measurements from the GNSS-R CubeSats and available ground-based GNSS receivers to derive Arctic vertical TEC (vTEC) maps. A simulation study using the model ionosphere constructed from the NeQuick-2 is conducted to assess the performance of the algorithm. Varying levels of temporal resolutions and solar activities, and the number of CubeSats and the number of maximum simultaneously tracked reflection signals by a CubeSat are implemented in the simulation. The results show that the inclusion of coherent GNSS-R measurements improves the accuracy of the vTEC maps under all levels of solar activities. The RMSE improvement percentage is most obvious when the update interval is the shortest. Increasing the number of CubeSats further improves the accuracy. However, no significant improvement in vTEC map accuracy is observed when the number of maximum simultaneously tracked GNSS-R satellites is higher than 4. Quantitative measures and analyses of the algorithm performances are presented in this article.

This article assesses the coherency of Global Navigation Satellite System (GNSS) signals reflected off the oceans and sea ice under grazing angle geometries and received aboard low Earth orbit (LEO) CubeSats for precision altimetry applications. The coherency is characterized as a function of ocean surface conditions and reflected signal parameters based on Spire Global CubeSat data collected from January to April 2019. The data contain 50-Hz GPS L1 and L2 carrier phase estimations obtained by open-loop tracking. Indicators based on the circular statistics of the excess-phase noise are developed to identify coherent and semicoherent reflections. Based on these indicators, we found that ~1% and 44% of GPS reflections over the ocean and sea ice, respectively, have potential for precision altimetry. The coherent and semicoherent reflection rates reach 23% in areas less than 200 km from the coastline and under calm sea conditions. Over young sea ice over the Arctic, this rate can be as high as 70%. There is a strong relationship between coherency and signal strength, and the coherency occurrence rate improves as the grazing angle decreases. The quality of the L1 and L2 coherent reflections is similar over sea ice, while, for reflections over the ocean, L1 signals are predominantly noisier and less coherent than the L2 signals. Using a postprocessing filtering method, the semicoherent reflections can achieve a similar level of altimetry precision as that of the coherent ones, thereby increasing the along-track length of the retrieved altimetry profile.

In this article, we investigate coherent global navigation satellite system reflectometry (GNSS-R) measurements obtained at the low earth orbits (LEOs) as a potential new data source for ionospheric total electron content (TEC) and ionospheric disturbance observations. Current global ionospheric TEC maps (GIMs) have limited spatial and temporal resolutions and accuracy due to lack of GNSS observations over oceans, polar caps, and inaccessible terrains. Our analysis of Spire Global’s CubeSat data indicates that coherent GNSS signals reflected off sea ice, inland water bodies, and calm ocean surface can be processed to achieve cm-level precision carrier phase estimations. Signal coherency is especially prevalent over sea ice where 41.7% reflections are coherent, compared to 4.3% in the overall dataset. This article presents the methodology to estimate slant TEC along the reflection signal ray path using coherent dual-frequency GNSS-R pseudoranage and carrier phase estimations obtained from low-cost CubeSats. The methodology is applied to Spire Global’s CubeSat data. The results show that the slant TEC retrieved from GNSS-R measurements and from GIM follow a similar trend. Moreover, the GNSS-R-based TEC time series offer a nearly “frozen in time” observation of the ionospheric structures due to the rapid scan velocity of GNSS-R rays across the ionosphere. The study demonstrates the potential of GNSS-R observations to fill the data gaps over the polar regions where space weather activities and TEC disturbances are most frequent and intense. Potential error sources and mitigation techniques are also discussed.

Coherent GNSS reflections over land predominantly occur over surface water bodies. This study presents a method to jointly use carrier phases and signal strengths of reflected signals to identify coherent reflections and applies it to the 50-Hz GNSS-R measurements from Spire Global Cubesats and CYGNSS microsatellites to map inland water bodies. A coherence detector was first developed using the circular statistics of carrier phase noises, identifying the input samples as coherent, semi-coherent, or incoherent. For any given track of data, we used this coherence detector to iteratively assess the coherency levels of the samples by a moving time window, then derived the coherency levels with the highest confidence. The circular statistics-based semi-coherent reflections with signal strengths above the prescribed threshold were regarded as coherent. The specular reflection points of the coherent reflections represent the locations of surface water. This method was applied to the Spire data to obtain the surface water extents for 1951 lakes and the CYGNSS data for 113 lakes. Compared to Global Surface Water Explorer observations, around 90% of the disagreements of the Spire data-based surface water boundaries are less than 0.73 km with a mean of 0.28 km and a standard deviation of 0.24 km. As for CYGNSS, ~90% of the disagreements are less than 0.43 km with a mean value of 0.18 km and a standard deviation of 0.16 km. The possible error sources are mainly fractional surface water, nearly flat and saturated ground surface, background land cover, and GNSS-R geometry.

This paper presents an evaluation of the relative sea ice surface heights retrieved using carrier phase measurements of coherent GNSS reflection signals recorded by Spire Global Inc.'s LEMUR-2 low-Earth orbit (LEO) cubeSats between January to April 2019. Coherent GNSS signal reflection usually occurs at relatively low elevation angles, and sea ice is a good reflector for GNSS signals. As analyzed in [1], most of the uncertainty for GNSS-R relative sea surface height (SSH) retrievals is from the tropospheric delay models, which usually have several centimeters error in the zenith total error (ZTD), and the effects will be significantly amplified at low elevation angles. In this paper, the retrieved sea surface height anomalies (SSHA) using LEMUR-2 GNSS-R data are compared with the monthly averaged ice freeboard measurements from ICESat-2. Overall, the comparison shows good consistency. However, for some reflection events/segments, adjustments of the zenith troposphere delay model of up to 11 cm is required in order to fit the ICESat-2 ice freeboard measurements. Therefore, the tropospehere delay correction may be a challenge for high-precision GNSS-R sea ice altimetry.

The carrier phase measurements of coherent Global Navigation Satellite Systems Reflectometry (GNSS-R)signals have demonstrated the potential for high-accuracy altimetry applications. However, the coherent components in the reflected signal are often accompanied by noncoherent scattered signals, which may cause numerous cycle slips in the conventional open-loop (OL) tracking and postprocessing approach. These cycle slips can lead to meter-level errors in the altimetry retrieval. This article presents a simultaneous cycle slip and noise filtering (SCANF) method for dual-frequency GNSS-R phase measurements generated by OL tracking. The performance of this method is demonstrated using real GNSS-R phase measurements recorded by receivers on board Spire’s low-Earth orbit (LEO) satellites. The retrieved sea surface height anomaly (SSHA) has an average root mean square (rms) of 7.3 cm for sea and sea ice surface reflections relative to the mean sea surface (MSS). The technique presented in this article is also applicable to GNSS carrier phase measurements obtained under other challenging conditions, such as signals propagating through ionosphere plasma structures, radio occultation (RO) signals traversing lower troposphere, and multipath-rich environments.

This article presents an adaptive hybrid-tracking (AHT) algorithm designed to process GNSS-R signals with a sufficient coherent component. Coherent GNSS-R signals have the potential to enable high-precision and high-resolution carrier-phase measurements for altimetry, sea-level monitoring, soil-moisture monitoring, flood mapping, snow-water equivalent measurements, and so on. The AHT algorithm incorporates the model inputs typically used in the master-slave open-loop (MS-OL) architecture into a closed-phase lock loop. Raw IF data recorded by the CYGNSS satellites over in-land water, land, and open-ocean surface are used to demonstrate the performance of the AHT. The results show that the AHT algorithm achieves comparable robustness with the MS-OL implementation while maintaining centimeter-level accuracy and excellent carrier-phase continuity that can be achieved with a fine-tuned Kalman filter (KF)-based adaptive closed-loop (ACL) system. Moreover, the AHT is suitable for real-time implementation and is applicable to other radio signals-of-opportunity.

Precise carrier phase measurements from coherent reflections of Global Navigation Satellite Systems (GNSS) signals are poised to enable new capabilities in Earth remote sensing. However, there is still much to learn about the reflection conditions that produce coherence. For land reflections especially, the degree to which various surface characteristics impact coherence is unclear. In this paper, we explore the dependence of coherence on four surface characteristics: maximum water extent, surface topography, soil moisture, and vegetation water content. To quantify the level of coherence, the phase is tracked from two sets of CYGNSS raw IF data and the circular length of the changes in phase is calculated. A strong link is found between coherence and the presence of surface water; the impact of the other surface characteristics on coherence is still under examination.

This paper presents two approaches to achieve high quality GNSS carrier phase estimations that can be implemented in bi-static receivers onboard low Earth orbiting satellites for precision altimetry applications. These two approaches are an adaptive hybrid open- and closed-loop tracking for single frequency GNSS receivers and an adaptive multicarrier tracking algorithm that optimally combines the outputs generated by multiple carrier tracking loop outputs. As a case study, raw GPS L1 intermediate frequency data collected by CYGNSS satellites are used to assess the adaptive hybrid carrier tracking algorithm performances. The results show that robust, accurate carrier tracking at cm-level precision is possible using a hybrid carrier tracking architecture. Analysis of the tracking results confirmed that low signal grazing angle, high antenna gain, and low wind speed over the ocean are necessary conditions for successfully carrier tracking.

This paper presents assessment on the coherency of reflected GPS signals received on a LEO satellite for high accuracy ocean altimetry applications. We analyze the coherent signal levels dependence on sea surface conditions and signal parameters based on GPS reflection data collected by Spire cubeSats between January and April 2019. The data contains carrier phase estimations obtained from an open-loop tracking process sampled at 50Hz for GPS carrier frequency L1 and L2. A conservative coherency quality test based on two circular statistics of the carrier phase measurements, circular-length and circular-kurtosis, is applied to the data. The results show that ~ 1% and ~40% of the events contain sufficient coherent energy for high precision altimetry applications over ocean and sea ice respectively.

This paper presents a support vector machine (SVM) -based detection method to identify coherent reflections in GNSS-R measurements. The data was collected by Spire low-Earth orbit (LEO) satellites during January to April, 2019, and it contains the In-phase (I) and Quadrature (Q) correlation outputs at 50 Hz from open-loop (OL) tracking process. The coherence detection is investigated based on 1100 labelled 1-second data segments. The detection results show that the SVM-based method achieves a detection accuracy of 98.66% and outperforms several other algorithms.

In this paper, we provide an analysis of radio frequency interference for global navigation satellite system reflectometry (GNSS-R) using multi-frequency global positioning system (GPS) data collected on Haleakala, Hawaii during a mountain-top radio occultation and reflection experiment conducted on May 6, 2017. The results show that the interferences on GPS L1 and L2 are continuous wave signals and occur at a 2 Hz rate. The interference on GPS L5 is pulsed signals originating from two aeronautical navigation systems. Moreover, the analysis reveals that the interference on GPS L1 can overwhelm the GNSS-R delay-Doppler map (DDM) if 1 ms coherent integration time is applied. Interference mitigation techniques are suggested for different types of interference on the three GPS frequency bands.

This paper presents a Kalman filter-based closed-loop carrier phase tracking algorithm and results of coherent GNSS-R signal from ocean and land surfaces using CYGNSS raw IF measurements. The carrier phase measurement from coherent GNSS-R signal allows centimeter level carrier phase altimetry. Closed-loop tracking of coherent reflection GNSS-R signal can provide higher resolution and accuracy estimates of signal parameters for other remote sensing applications, e.g., SNR measurements for land surface monitoring, than non-coherent measurements.