Chinese BeiDou Navigation Satellite System (BDS) as a mixed constellation, consists of not only Medium Earth Orbit (MEO) satellites but also Inclined Geosynchronous Orbit (IGSO) and Geostationary Earth Orbit (GEO) satellites, of which the GEO satellites remain visible and stationary in the Asia- Pacific region almost all the time so as to better ensure the reflected signals' stability and continuity, compared to using only MEO satellites in previous GNSS-R remote sensing research. This paper demonstrates ocean altimetry capability using reflected signals from BDS GEO satellite with coastal experiments conducted in Weihai, Shandong, China on July 6 and July 9, 2019. By using only one GEO satellite, the precision of DDM (Delay Doppler Map) and phase altimetry is up to decimeter (close to millimeter) level. And the results show that BDS GEO- R technique can be used to monitor small changes in ocean altimetry with high temporal resolution.

This article proposes a new sea surface wind speed (SSWS) retrieval modeling algorithm based on the empirical orthogonal function (EOF) analysis for observations acquired by the global navigation satellite system reflectometry (GNSS-R). As a nonparametric modeling algorithm, it is simpler compared with the nonlinear methods. The influence of wind speed and incident angle on the modeling error is analyzed for the first time using a spectrum analysis. Three types of data from 80% CYGNSS 2019–2020 observations [delay Doppler map average (DDMA) and leading edge slope (LES)], signal incident angle, and the European Centre for Medium-Range Weather Forecasts Reanalysis V5 (ERA5) reference wind speed are used in the EOF analysis to establish two retrieval models. The remaining 20% of the data are used for accuracy evaluation after getting the final wind speed by the minimum variance (MV) estimator. As a result, when using three 0–20-m/s wind speeds of ERA5, Advanced Scatterometer (ASCAT), and the Modern-Era Retrospective Analysis for Research and Applications V2 (MERRA2) as contrasts, the root mean squared errors (RMSEs) are 1.51, 1.45, and 1.43 m/s, respectively. Compared with CYGNSS wind product, the performance of this algorithm is closer to the L2 Climate Data Record (CDR) V1.1 product than V1.0. The results demonstrate that the EOF algorithm has a good performance in retrieving SSWS and can better retain the influence of the incident angle on the observations.

Global Navigation Satellite System (GNSS) signals generate slant tropospheric delays when they pass through the atmosphere, which is recognized as the main source of error in many spatial geodetic applications. The zenith tropospheric delay (ZTD) derived from radio occultation data is of great significance to atmospheric research and meteorology and needs to be assessed in the use of precision positioning. Based on the atmPrf, sonPrf, and echPrf data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) Data Analysis and Archiving Center (CDAAC) from 1 January to 31 December 2008 and 2012, we obtained the ZTDs of the radio occultation data (occZTD) and the corresponding radiosonde (sonZTD) and ECWMF data (echZTD). The ZTDs derived from ground-based global positioning system (GPS) observations from the International GNSS Service (IGS) were corrected to the lowest tangent point height of the matched radio occultation profile by the barometric height formula (gnsZTD). The statistical results show that the absolute values of the bias between occZTD and echZTD, sonZTD, or gnsZTD are less than 5 mm, and the standard deviations are approximately 20 mm or less, indicating that occZTD had significant accuracy in the GNSS positioning model even when the local spherical symmetry assumption error was introduced when the Abel inversion algorithm was used to obtain the refractive index profile of atmPrf. The effects of the horizontal/vertical matching resolution and the variation in the station height/latitude on the biases of occZTD and gnsZTD were analyzed. The results can be used to quantify the performance of radio occultation data for tropospheric delay error correction in dynamic high-precision positioning.

The ionospheric mapping function (IMF) is fundamental in retrieving total electron content (TEC) from observations on board low earth orbiting (LEO) satellites, as well as the receiver differential code bias (DCB) estimation. Most IMFs apply the assumption that the electron density field is spherical symmetric, only dependent on the elevation angle of signal ray path without considering the azimuthal diversity. However, the ionospheric horizontal asymmetry may introduce large mapping errors in slant to vertical TEC conversion or vice versa especially at low elevation angles. This study investigates the variations of the horizontal gradients in the topside ionosphere and plasmasphere, and proposes a formalism for parametrizing the time, location, elevation and azimuth angle dependent horizontal gradients based on the Global Core Plasma Model (GCPM). Several parameters are estimated to represent the north-to-south, east-to-west asymmetric patterns of slant TEC and the horizontal mapping factor with varying elevation angle. Results show the empirical model of the horizontal gradients are well constructed and contribute positively to reducing the mapping error of vertical TEC. The root-mean-square error (RMS) at all elevation angles are decreased to 0.5 TECU and 1.0 TECU under low and high solar activity conditions respectively. This approach is potential to be used in the absolute GNSS/LEO TEC and DCB estimation and topside ionosphere/plasmasphere exploration.