Positioning of spacecraft (e.g., geostationary orbit (GEO), high elliptical orbit (HEO), and lunar trajectory) is crucial for mission completion. Instead of using ground control systems, global navigation satellite system (GNSS) can be an effective approach to provide positioning, navigation and timing service for spacecraft. In 2020, China finished the construction of the third generation of BeiDou navigation satellite system (BDS-3); this global coverage system will contribute better sidelobe signal visibility for spacecraft. Meanwhile, with more than 100 GNSS satellites, multi-GNSS navigation performance on the spacecraft is worth studying. In this paper, instead of using signal-in-space ranging errors, we simulate pseudorange observations with measurement noises varying with received signal powers. Navigation performances of BDS-3 and its combinations with other systems were conducted. Results showed that, owing to GEO and inclined geosynchronous orbit (IGSO) satellites, all three types (GEO, HEO, and lunar trajectory) of spacecraft received more signals from BDS-3 than from other navigation systems. Single point positioning (SPP) accuracy of the GEO and HEO spacecraft was 17.7 and 23.1 m, respectively, with BDS-3 data alone. Including the other three systems, i.e., GPS, Galileo, and GLONASS, improved the SPP accuracy by 36.2% and 19.9% for GEO and HEO, respectively. Navigation performance of the lunar probe was significantly improved when receiver sensitivity increased from 20 dB-Hz to 15 dB-Hz. Only dual- (BDS-3/GPS) or multi-GNSS (BDS-3, GPS, Galileo, GLONASS) could provide continuous navigation solutions with a receiver threshold of 15 dB-Hz.

Filtering is a necessary step in the Gravity Recovery and Climate Experiment (GRACE) data processing, but leads to signal leakage and attenuation obviously, and adversely affects the quality of global and regional mass change estimates. We propose to use the Tikhonov regularization technique with the L-curve method to solve a correction equation which can reduce the leakage error caused by filter involved in GRACE data processing. We first demonstrate that the leakage error caused by the Gaussian filter can be well corrected by our regularization technique with simulation studies in Greenland and Antarctica. Furthermore, our regularization technique can restore the spatial distribution of original mass changes. For example, after applying the regularization method to GRAEC data (2003-2012), we find that GRACE mass changes tend to move from interior to coastal area in Greenland, which are consistent with recent other studies. After being corrected for glacial isostatic adjustment (GIA) effect, our results show that the ice mass loss rates were 274 ± 30 and 107 ± 34 Gt/yr in Greenland and Antarctica from 2003 to 2012, respectively. And a 10 ± 4 Gt/yr increase rate in Greenland interior is also detected.

The discrepancy in the observed global mean sea level budget increased significantly since 2016, but the budget discrepancy over basin‐scales is unclear. In this contribution, we investigate the sea level budget discrepancies in major basins with observations from satellite altimetry, satellite gravimetry, and Argo floats. During 2016–2020, we find substantial discrepancy of 5.72 ± 0.98 mm/yr over the North Atlantic Ocean, and the basin scale discrepancies are smaller elsewhere. Our analysis suggests that three factors, including the wet tropospheric correction (WTC) effect, deep ocean warming signal, and the contemporary ocean bottom deformation (OBD), together reduce the discrepancy by only 1 mm/yr for the North Atlantic Ocean. We decompose sea level observations into the spherical harmonic domain and observe increased discrepancy in low‐degree variations of C₁₀ and C₂₁ since 2016. These two coefficients result in a contrasting signal between the North and South Atlantic Ocean and contribute to the large discrepancy over the North Atlantic Ocean. We further demonstrate that the C₁₀ and C₂₁ discrepancies are independent of the three factors. However, we find regional salinity biases in the Argo data that reduce the discrepancy for the North Atlantic Ocean. Our findings add to the debate about recent sea level budget and imply that further analysis of the Argo North Atlantic data set may be useful.