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Compared to conventional spoofing, emerging spoofing attacks pose a heightened threat to security applications within the global navigation satellite system (GNSS) due to their subtly designed signal structures. In response, a novel spoofing detection method entitled aggregated correlation residue likelihood analysis (A-CoRLiAn) is proposed in this study. Requiring only the addition of a pair of supplementary correlators, A-CoRLiAn harnesses correlation residues to formulate a likelihood metric, subsequently aggregating weighted decisions from all tracked satellites to ascertain the presence of spoofing. Evaluated under six diverse spoofing scenarios (including emerging challenges) in the Texas Spoofing Test Battery (TEXBAT) via Monte Carlo simulations, A-CoRLiAn yields a detection rate of 99.71%, demonstrating sensitivity, robustness, autonomy, and a lightweight architecture conducive to real-time implementation against spoofing threats. [ABSTRACT FROM AUTHOR]

Precision point positioning (PPP) utilizing the Global Navigation Satellite System (GNSS) is a traditional and widely employed technology. Its performance is susceptible to observation discontinuities and unfavorable geometric configurations. Consequently, the integration of the Inertial Navigation System (INS) and GNSS makes full use of their respective advantages and effectively mitigates the limitations of GNSS positioning. However, the GNSS/INS integration faces significant challenges in complex and harsh urban environments. In recent years, the geometry between the user and the satellite has been effectively improved with the advent of lower-orbits and faster-speed Low Earth Orbit (LEO) satellites. This enhancement provides more observation data, opening up new possibilities and opportunities for high-precision positioning. Meanwhile, in contrast to the traditional extended Kalman filter (EKF) approach, the performance of the LEO-enhanced GNSS/INS tightly coupled integration (TCI) can be significantly improved by employing the factor graph optimization (FGO) method with multiple iterations to achieve stable estimation. In this study, LEO data and the FGO method were employed to enhance the GNSS/INS TCI. To validate the effectiveness of the method, vehicle data and simulated LEO observations were subjected to thorough analysis. The results suggest that the integration of LEO data significantly enhances the positioning accuracy and convergence speed of the GNSS/INS TCI. In contrast to the FGO GNSS/INS TCI without LEO enhancement, the average enhancement effect of the LEO is 22.16%, 7.58%, and 10.13% in the north, east, and vertical directions, respectively. Furthermore, the average root mean square error (RMSE) of the LEO-enhanced FGO GNSS/INS TCI is 0.63 m, 1.21 m, and 0.85 m in the north, east, and vertical directions, respectively, representing an average improvement of 41.91%, 13.66%, and 2.52% over the traditional EKF method. Meanwhile, the simulation results demonstrate that LEO data and the FGO method effectively enhance the positioning and convergence performance of GNSS/INS TCI in GNSS-challenged environments (tall buildings, viaducts, underground tunnels, and wooded areas). [ABSTRACT FROM AUTHOR]

The Beidou-3 system (BDS-3) satellites are deployed, equipped with an inter-satellite link (ISL) payload, so that the satellite–satellite or satellite-ground time synchronization is available. The satellite-ground link (GSL) can be used in conjunction with the ISL if proper attention is paid to all corrections and the biases are fitted. We execute methods to synchronize the clocks of BDS-3 satellites to an accurate reference clock on the ground, by estimating relative clock offsets obtained via Ka-band GSL observations. We solve for the relative biases using the closure properties of the redundant biases and the Ka-band (Ka-mode) satellite-ground two-way data. We find the biases, relative to the GSL hardware delay, are relatively stable in the short term. This makes it feasible to estimate them as a constant every few hours, and the standard deviation of the hardware delay estimations within 24 h is slightly less than 0.7 ns. The frequency stability of Ka-mode estimated clock offset shows a negative short-term performance because of the dominant effect of the white phase noise in the relative clock offsets from the Ka-mode, but the long-term performance seems to be improved to a higher level. The time synchronization accuracy of Ka-mode is proven to be better than 0.3 ns (RMS), whereas the accuracy for the high-orbit satellite is slightly worse. [ABSTRACT FROM AUTHOR]