Addressing the challenge of extracting coseismic offset signals from GNSS coordinate time series using earthquake catalog information, this study introduces a method based on optimized window and component selection in Singular Spectrum Analysis (SSA). The proposed approach automatically selects relevant components for time series reconstruction according to the magnitude of eigenvalues and the contribution rate of each component, without relying on prior information or assumptions. This effectively overcomes the limitations associated with arbitrary decomposition and reconstruction of time series in conventional SSA. By subtracting the reconstructed series from the original data, a residual time series is obtained, from which reliable offset signals can be extracted as comprehensively as possible. Through simulation tests and an application to the March 9, 2011, Mw7.3 earthquake event in Japan, comparative experiments were conducted to evaluate different window lengths and varying numbers of reconstructed components. The results indicate that a window length of 365 days, combined with the selection of principal components whose cumulative contribution rate exceeds 95%, constitutes the most suitable strategy for detecting offset signals in GNSS residual time series.
Fault detection and identification algorithm is essential to ensure the reliability of global navigation satellite systems (GNSS) systems for high-precision intelligent applications. Low-cost receivers always suffers from GNSS pseudorange gross-error detection and carrier-phase cycle-slip anomaly in complex environments, which would degrade positioning accuracy. To address these issues, this paper proposes an enhanced low-cost RTK precise-positioning algorithm with an adaptive strategy, designed to detect multiple pseudorange gross errors and carrier-phase cycle slips. By leveraging time differenced darrier phase (TDCP) observations, the proposed method dynamically adjusts detection thresholds in real time, thereby minoring multiple faults and improving positining accuracy. To evaluate the performance of the proposed algorithm, a dynamic vehicle experiment equipped with ublox and BeiYun low-cost GNSS devices was conducted. Four schemes including GL, GLF, GLFTC, and GLFTA methods are compared. Results show that the 3D RMS positioning errors of the proposed GLFTA method achieves maximum 19.34% improvement. That is because the proposed GLFTA method incorporating an adaptive strategy can detect small carrier phase cycle slips than the GL, GLF, and GLFTC methods, thereby enhancing RTK positioning performance in complex environments.
Our study employs GPS coordinate time series and the NIF method to invert postseismic deformation, investigate the spatiotemporal evolution of fault slip, and evaluate the inversion efficiency of the NIF method under various parameter settings, thereby providing prior information for future research on earthquakes and fault slip. Taking the GPS coordinate time series from the Tokai region of Japan during 2009-2021 as an example, we conducted an analysis using the NIF method. The results indicate that the fault slip following the 2011 earthquake was primarily concentrated in the northeastern part of Tokai region (34.8°N-35.8°N, 137.2°E-138.4°E), with a maximum cumulative slip of 9.31 cm at depths ranging from 20 to 60 km. In terms of model parameter analysis, the inversion time and memory cost increase with the number of sub-faults, while the maximum cumulative slip approaches a stable value. Variations in the proportion of local benchmark motion proportion parameter do not affect the inversion time or memory cost but are negatively correlated with the maximum cumulative slip. The time scale of the GPS coordinate time series has no significant impact on the NIF inversion. In contrast, higher time resolution of the GPS coordinate time series results in longer inversion times and greater memory cost, with the maximum cumulative slip gradually stabilizing.
Addressing the inaccuracies in the ground-calibrated phase center offsets (PCOs) provided by the China Satellite Navigation Office (CSNO) for BeiDou-3 (BDS-3) satellites and the absence of phase center variations (PCVs), this study performs in-orbit calibration of the B1C/B2a antenna phase centers for BDS-3 MEO and IGSO satellites under the IGS20 frame. Using ionosphere-free combination observations from 155 global IGS/MGEX stations spanning 2021 to 2024, we demonstrate high consistency in PCV estimates for satellites of the same type, with most nadir-angle PCV differences below 1 mm and an overall standard deviation of approximately 0.3 mm. Horizontal PCO estimates align with igs20.atx values at the centimeter level. After aligning the Z-PCO estimates with the IGS20 frame, the mean differences with respect to the igs20.atx values are -9.5 cm for MEO satellites and 40 cm for IGSO satellites. Compared to the igs20.atx model, the phase center correction (PCC) model derived in this study improves the orbit overlap accuracy for BDS-3 MEO satellites by 0.43% to 7.03%. Furthermore, using the estimated B1C/B2a PCC model, the mean scale factor difference for BDS-3 solutions relative to the IGS20 frame is 0.16 ppb, confirming successful alignment with IGS20. The BDS-3 PCC results have been submitted to the International GNSS Service (IGS) through the Chinese Academy of Sciences (CAS) Analysis Center, contributing to integrated analysis and promoting the high-precision international application of the BeiDou Navigation Satellite System.
With the arrival of the maximum phase of Solar Cycle 25, ionospheric scintillation phenomena have become increasingly frequent, which severely impacts the capabilities of GNSS positioning, navigation, and timing services. This study collected 30-second sampling rate data from 6 GNSS stations in low-latitude regions of Asia, Oceania, the Pacific, Africa, and South America spanning the period 2014-2024. Using S4c as the criterion for identifying low-latitude amplitude ionospheric scintillation, the statistical characteristics of ionospheric scintillation in various regions were analyzed. The results demonstrated a significant positive correlation between the occurrence of ionospheric scintillation in various regions and solar activity. During solar maximum years, ionospheric scintillations at the KOUG station mainly occurred in winter, spring, and autumn, while those at the other stations are predominantly observed in spring and autumn annually. Scintillation at all stations predominantly takes place between 8:00 p.m. and 2:00 a.m. local time. In low solar activity years, both the frequency and duration of ionospheric scintillation at each station decrease significantly. With the exception of the KOUG station, where scintillation remained severe, the other stations show no obvious seasonal or local time patterns. The directional distribution of ionospheric scintillation exhibits a distinct relationship with the latitude of the stations. Furthermore, the study indicates that due to the distinct meridional distribution characteristics and latitude-dependent variations of equatorial plasma bubbles, the scintillation intensity at different locations during high solar activity years follows the order from strongest to weakest: South America (near the Atlantic Ocean), Africa, the Pacific region adjacent to South America, Asia, and Oceania.
