The GNSS spoofing jamming is generated by transmitting spoofing signals that are identical or similar to the authentic satellite signals but have a stronger power in order to guide a receiver to acquire and track them instead of real signals. The main aim of spoofing is to make the receiver obtain wrong timing and positioning information. In this paper, the characteristics of spoofing signals in the acquisition phase are analyzed and studied. Based on the idea of confrontation evolution of a general adverse network (GAN), this study proposes a GNSS anti-spoofing method. The performance of the proposed method is verified by simulations experiments. The experimental results show that when the pseudo-code phase difference between the spoofing signal and the authentic signal exceeds 0.5 chip, the detection probability of the GAN can reach more than 98%. The proposed method can also be applied to situations where the spoofing signal is highly synchronized with the real signal.

Global navigation satellite system (GNSS) spoofing interference poses a great threat to the security of end users. Based on the same propagation path characteristics of the spoofing signals transmitted by a single antenna spoofing device, this paper proposes a method against single antenna spoofing jamming utilizing the Fréchet distance of Doppler frequency difference. When the receiver moves, the Doppler data in a window are fitted via the leastsquares method, and the Fréchet distance between the two satellite signals is calculated to obtain the similarity evaluation value between them. The detection of spoofing signal is carried out based on the evaluation value. We use real data to verify the detection performance of the method, and the experimental results show that the method can effectively distinguish the spoofing signal from the authentic signal. In addition, the method has low computational complexity and requires less additional information, which makes it possible to apply it in the anti-spoofing module of a GNSS receiver.

With the widespread application of GNSS systems in various fields, the problem of spoofing detection has drawn much attention from the satellite navigation community. The GNSS spoofing interference generally uses fake or replayed satellite signals to make the targeted receivers receive false GNSS signals and reduce the accuracy of calculated position and time information. In order to ensure and improve the security of GNSS services, in recent years, academia and industry have studied the spoofing detection technology from multiple aspects, and many theoretical results have been obtained. This paper starts the analysis from the acquisition phase of a receiver and analyzes the characteristics of the small-delay spoofing signal. Aiming at solving the problem that it is difficult to detect small-delay (0–2 chips) spoofed signals during the acquisition phase, the CNN (Convolutional Neural Network) based method is used to detect the small-delay spoofed signals effectively. According to the experimental simulation results, when the code phase difference between the spoofing signal and the authentic satellite signal is larger than 0.5 code chip, the CNN-based method achieves high detection accuracy. In addition, the algorithm can quickly detect the data without using any additional equipment. Therefore, low complexity is achieved. This makes the algorithm has a good engineering application prospect.

The widespread availability of high-performance clocks has motivated interest in time scale algorithms. There are various time scale algorithms in use today, ranging in application from scientific to commercial. The weighted average algorithm has been widely used to generate an ensemble time scale. It takes one weight for each clock according to the stability or predictability to generate the ensemble time scale. However, one weight cannot reflect the long-term, mid-term and short-term stability performance of the clock simultaneously. Therefore, it cannot improve the long-term, mid-term and short-term stability at the same time. To solve this problem, a multi-dimensional weighted average algorithm is proposed in this paper, which decomposes the clock difference into three dimensions and gets weights in three dimensions to give consideration to improve long-term, mid-term and short-term stability simultaneously. The final results of simulation and experiment demonstrate that the algorithm proposed in this paper improved Allan deviations of 3.94 × 10⁻¹⁵ on daily and 7.86 × 10⁻¹⁵ on monthly averaging times with respect to those obtained from AT1 and ALGOS, respectively.

Based on BeiDou navigation satellite system (BDS), the Quasi-Zenith satellite system (QZSS) was added to assist in studying the precise point positioning (PPP) time and frequency transfer effect. Ambiguity resolution (AR) is the key to the rapid conversion of the PPP method. Therefore, this paper also used the ionospheric-free combination and the observable-specific signal bias (OSB) product of Wuhan University to test the time–frequency transfer effect of BDS ambiguity-fixed. In this way, BDS PPP, BDS + QZSS PPP, BDS PPP-AR, and global positioning system (GPS) PPP methods were formed. Six stations located in Japan and Australia were selected for experiments. Conclusion: BDS can reach the same level as GPS; when the cut-off angle is greater than 15°, adding QZSS could improve the success rate, accuracy, and frequency stability of the solution of time links effectively; the ambiguity fixed strategy can improve the time transfer accuracy but not the short-term frequency stability.