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Global navigation satellite systems (GNSSs) are widely used in various fields to provide high-precision timing. However, their low signal power and open signal structure render GNSS receivers vulnerable to time synchronization attacks (TSAs). In this study, we propose a novel single-antenna-based TSA mitigation algorithm. First, a multicorrelator estimator was adopted to calculate the parameters of the authentic and counterfeit signals. Then, the predicted pseudorange was derived for spoofing validation, and the counterfeit signals were subtracted. Finally, a robust extended Kalman filter was adopted to resist gross errors in the estimation results. A series of Monte Carlo simulations were conducted to evaluate the performance of the proposed method with different relative delays and power advantages of the spoofing signals. The Texas Spoofing Test Battery spoofing datasets were used in the experiments to verify the effectiveness of the proposed algorithm. The results indicated that the timing errors decreased from $2.0~\mu \text{s}$ (600 m) to 53.4 ns (16 m), and the spoofing signals were considerably mitigated. The proposed anti-spoofing algorithm can ensure the availability of GNSS timing under TSAs and only requires a single antenna, greatly simplifying the GNSS receiver installation and reducing costs.

Satellite navigation spoofing has become a central issue of jamming technology research because of its serious threat and ability to conceal itself. Increasingly, targets are equipped with more robust GNSS/IMU systems and normalized innovation squared (NIS) is used to detect interference. Therefore, it is harder to implement covert trajectory spoofing on a GNSS/IMU system than a GNSS-only target. In practice, spoofing is needed to control unknown targets. Therefore, covert trajectory spoofing for GNSS/IMU targets is an important issue. Hence, using the information fusion of a GNSS/IMU system, the influence of spoofing on loosely coupled GNSS/IMU positioning is derived. To avoid ill-posed equations when introducing a measurement deviation, a Kalman gain matrix local regularization method is proposed to accurately determine the measurement deviation. To avoid triggering the NIS detection alarm, the range that enables the introduced measurement deviation to remain concealed is calculated. Then, a two-step trajectory guidance algorithm is proposed to quickly guide the target onto the spoofing trajectory. The simulation results show that the proposed trajectory spoofing algorithm can guide a loosely coupled GNSS/IMU target along a spoofing trajectory without triggering the NIS detection alarm. The proposed method can remain concealed and has good theoretical and practical application value.

Owing to the nonlinearity in visual-inertial state estimation, sufficiently accurate initial states, especially the spatial and temporal parameters between IMU (Inertial Measurement Unit) and camera, should be provided to avoid divergence. Moreover, these parameters are required to be calibrated online since they are likely to vary once the mechanical configuration slightly changes. Recently, direct approaches have gained popularity for their better performance than feature-based approaches in little-texture or low-illumination environments, taking advantage of tracking pixels directly. Based on these considerations, we perform a direct version of monocular VIO (Visual-inertial Odometry), and propose a novel approach to initialize the spatial-temporal parameters and estimate them with all other variables of interest (IMU pose, point inverse depth, etc.). We highlight that our approach is able to perform robust and accurate initialization and online calibration for the spatial and temporal parameters without utilizing any prior information, and also achieves high-precision estimates even when large temporal offset occurs. The performance of the proposed approach was verified through the public UAV (Unmanned Aerial Vehicle) dataset.