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Abstract Satellite navigation positioning has become an indispensable component of everyday life, where precise pinpointing and rapid convergence are crucial in delivering timely and accurate location information. However, due to the damping of integer ambiguities and system residual errors, the rapid convergence of Precise Point Positioning (PPP) implementation is a significant challenge. To address this, this paper proposes a novel Carrier Phase Zero-Baseline Self-Differencing Precise Point Positioning (CZS-PPP) technique and its ionosphere-free fusion model. By employing the proposed CZS-PPP approach in separate scenarios involving BDS-3, GPS, and dual-system settings, we systematically validate the efficacy of the method. The experimental results indicate that the convergence time of the method is less than 4 min in a single-system scenario. Furthermore, in a dual-system scenario, the method can achieve rapid convergence in less than 3 min. The CZS-PPP technique presented demonstrates the elimination of integer ambiguities and the effective suppression of system residuals, in comparison to the conventional method. The proposed approach has demonstrated remarkable performance across different systems, offering a promising new pathway for achieving PPP fast convergence in BDS/GNSS.

Spoofing poses a serious security threat to the satellite navigation system. Most of the current spoofing detection methods are based on the information in the receiver-solving process. Applying the above spoofing detection algorithm on the receiver requires a redesign of the original receiver, which limits the application of the deceptive detection method on the ex-factory receiver. In the case of single-station spoofing, the positions of the successfully spoofed multiple receivers are the same according to the deception signal, but the clock offset is different. The single-difference clock offset is positively correlated with the distance between the two receivers. Based on the above principles, this paper proposes a spoofing detection and spoofing direction method based on the positioning solutions of three receivers. The observation value of the baseline length is calculated from the position information in the positioning solution, and spoofing detection is realized by hypothesis testing. The clocks of the three receivers are synchronized. The Adaptive Delta Gradient Descent(ADGD) method is adopted to calculate the spoofing direction according to the single-difference clock offset in the positioning solution. The direction angle is optimized through the Interacting Multiple Model based on the volume Kalman Filter. The relationship between several parameters and the direction accuracy of spoofing is analyzed through simulation tests. Experimental results show that this method can effectively detect and orient spoofing. In addition, the detection and orientation method of spoofing has the advantage of fast response speed, which can realize fast spoofing detection and direction finding in a deception environment.

Spoofing against the Global Navigation Satellite System (GNSS) is an attack with strong concealment, posing a significant threat to the security of the GNSS. Many strategies have been developed to prevent such attacks, but current detection methods based on signal direction for multi-agent spoofing require multiple antennas/receivers, leading to increased cost and complexity in implementation. Additionally, methods utilizing a moving single antenna cannot effectively detect multi-agent spoofing. Therefore, we introduce a novel spoofing-detection technique based on the intersection angle between two directions of arrival (IA-DOA) using a single rotating antenna. The essence of this approach lies in estimating the IA-DOA between a pair of signals by utilizing the carrier-to-noise ratio (CNR) and carrier phase single difference (CPSD) of the received signal. The estimation of IA-DOA should be consistent with the prediction when there is no spoofing. With spoofing, it is difficult to accurately simulate the directionality of navigation signals, which can disrupt the consistency between the estimation and prediction of IA-DOA. Therefore, estimations and predictions of IA-DOA can be used to establish detection variables through generalized likelihood ratio testing (GLRT) to detect multi-agent spoofing. We conducted a simulation to analyze the impact of the antenna’s parameters on the detection performance and evaluated it through on-site experiments. The results indicate that the method proposed in this article can efficiently achieve real-time detection of multi-agent spoofing.