Tianlin Wang

This work develops a methodology for using commanded roll maneuvers by Cyclone Global Navigation Satellite System (CYGNSS) constellation observatories to improve the determination of the nadir antenna patterns that receive GNSS signals reflected from Earth’s surface. The method relies on observation geometry properties in differing roll states that are used as a diagnostic tool to reveal Level-1 calibration errors associated with prelaunch mis-characterization of the nadir antenna patterns and as numerical constraints on algorithms to derive improved patterns that are more representative of in-orbit gain levels. It is shown that the updated gain estimates differ by -3 to 3 dB in a non-uniform fashion. In the companion work (Part III), the effects the use of these updated patterns has in terms of advancing the consistency of the calibration quality of observables is explored. Initial assessments presented here highlight how observable anomalies attributable to inconsistencies in the characterization of in-orbit nadir may be reduced by over 50% using the proposed methodologies.

To maintain a healthy power budget, observatories in the Cyclone Global Navigation Satellite System (CYGNSS) constellation routinely undertake commanded roll maneuvers as a means of increasing the exposure of their solar panels to sun-light thereby boosting power generation levels while continuing normal science operations, in particular Level-1 measurements and related downlinking. The current work (Part I) demonstrates how these roll maneuvers can be leveraged to improve the calibration quality of critical Level-1 observables, achieved primarily through the determination of zenith antenna gain patterns, which receive the direct GPS signals, and GPS transmitter gain tables. In the companion works (Part II and Part III), emphasis is placed on leveraging related techniques to determine the nadir antenna patterns, which receive the reflected GPS signals and the assessing impacts updates have on observables. This is enabled by the unique measurement properties that arise, due to periodicities in observation geometries, when the satellites are rolled compared to their nominal non-rolled state. The proposed technique leads to non-uniform corrections to the CYGNSS zenith antenna patterns by up to 4 dB relative to prior estimates. Uncertainties in the Effective Isotropic Radiated Power (EIRP) of the GPS transmissions are reduced by an average of 33%. The calibration improvements highlight the efficacy of leveraging ‘rolled data’ for deriving GPS transmitter patterns as well as demonstrating that data records as short as a single day can be used with as little as 4% uncertainty in the resulting improvement.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

The NASA-ISRO Synthetic Aperture Radar (NISAR) mission will advance global soil moisture monitoring through high-resolution L-band observations. However, accurate fine-scale retrieval remains challenging due to the 12-day revisit interval and complex, scale-dependent influences of vegetation and surface roughness on backscatter. This study introduces the SMAP-AVS (Attenuation-Volume scattering-Surface scattering) model, a semi-empirical framework evaluated using ALOS-2 PALSAR observations. Formulated within the Water Cloud Model framework, the methodology moves beyond conventional land-cover-based parameters by adopting pixel-wise parameterization. Leveraging soil moisture temporal stability, the framework assumes strong correlation between coarse-scale (9 km) SMAP L3 products and fine-scale (1 km) variations, enabling separation of vegetation and surface roughness contributions to the SAR signal. The SMAP-AVS framework is resolution-agnostic; while demonstrated at 1 km, it scales to meter-resolution expected from NISAR. Once parameterized, the model operates in snapshot retrieval mode, deriving soil moisture from single SAR acquisitions and NDVI data without further temporal information. Validation across four hydro-climatically diverse U.S. regions (2021–2024) included temporal comparison against International Soil Moisture Network observations and spatial validation using Multi-Radar Multi-Sensor precipitation fields to distinguish physical moisture heterogeneity from artifacts. SMAP-AVS resolves rainfall-driven patterns often missed by coarser products, with spatial correlation coefficients exceeding 0.5 in semi-arid and agricultural regions, demonstrating that the framework captures physically significant hydrological variability and offers a scalable methodology for operational high-resolution soil moisture products.

As part of the continued refinement of the Cyclone Global Navigation Satellite System (CYGNSS) mission’s Level-1 calibration practices, this work reports on recent progress to compensate for thermal artifacts associated with reported Effective Isotropic Radiated Power (EIRP) tracked by the receivers’ zenith channels in the form of oscillations with a dominant 40-60 day principal component. The use of the uncorrected EIRPs in the calibration of Normalized Bistatic Radar Cross Section (NBRCS) estimates is shown to lead to commensurate non-geophysical oscillations. A simple scheme for using in-orbit measurements to rederive prelaunch zenith channel LNA gain tables as a function of the relevant temperature is overviewed. These are subsequently used as part of the EIRP calibration process and to implicitly correct reported NBRCS estimates. The corrected NBRCS estimates are markedly more consistent. It is estimated that the revisions introduced as part of this work, and adopted for the mission’s latest v3.2 Level-1 data release, reduce the errors in the temperature dependence of the transmitter power estimates by an average of 88% while also reducing NBRCS relative spectral densities over the relevant frequency components by an average of 36%. The remaining energy is attributed to a combination of smaller residual, unaccounted for, calibration imperfections but more importantly to real geophysical phenomena causing oscillations over similar time scales whose minimization is not of interest.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

The NASA CYGNSS mission is a constellation of 8 small satellites that receive GPS signals reflected off the Earth to support a variety of science applications. For remote sensing, the strength of the reflected GPS signal contains important information and must be known to a small fraction of a dB. This makes it very different than traditional GPS navigation applications in which small amplitude variations have minor or negligible impact depending on the accuracy requirements of the specific application. Satisfying mission requirements necessitates precise knowledge of the GPS satellite transmit antenna pattern and the receive antenna pattern on each CYGNSS satellite. In this paper, we present the antenna calibration approach that is used by the CYGNSS science operations center. GPS satellite and CYGNSS satellite antenna patterns are jointly estimated using several years of on-orbit CYGNSS measurements. The orbiting GPS transmit and CYGNSS receive antennas form a spaceborne antenna measurement range which can be utilized to determine their patterns. The accuracy of the estimated antenna patterns can then be quantified using CYGNSS GPS science data as a metric. When compared to the limited publicly-available GPS satellite antenna data or antenna chamber measurements of the CYGNSS satellites, the proposed on-orbit approach is able to introduce corrections that significantly improve the CYGNSS mission science performance.