Traction spoofing is an important component of Global Navigation Satellite System (GNSS) intermediate attacks, and the traction scheme directly determines the concealment of spoofing. However, spoofing via conventional traction strategies can be easily detected using Time of Arrival (TOA) and power detection. Based on a BPSK-modulated signal, a novel traction strategy using traction code is proposed to suppress part of the authentication signal and form an ideal correlation peak. This strategy was modeled and simulated to verify its theoretical feasibility. Effective spoofing data were generated based on the signal generation software to verify the spoofing effect with the reception of the software receiver. It can be inferred that no significant distortion occurred throughout the traction process, and the value range of the traction speed was expanded. The received results in different scenarios demonstrated that the observations’ Root-Mean-Square Error (RMSE) percentage change in the proposed strategy is significantly better than those of conventional strategies. A Ratio Test was also performed, verifying that the strategy can bypass Signal Quality Monitoring (SQM) detection. Meanwhile, the proposed strategy remained effective when the $\mathrm{C}/{\mathrm{N}}_0$ increased to 60 dBHz. In summary, the proposed strategy exhibits destructiveness, concealment, and adaptability on the battlefield.

Demand for Global Navigation Satellite System (GNSS) applications in the urban environment has experienced a remarkable growth in recent years. However, the received signals are subjected to various urban channel impairments, like shadowing and multipath fading. Therefore, the decoding performance is different from that in open-sky conditions. In this paper, a two-state Land Mobile Satellite (LMS) channel based on the Markov process is used to model the urban channel properties, and then, the analysis of decoding performance in terms of frame error rate (FER) in the LMS channel is performed by evaluating the effect of three major influencing factors, specifically, coding and interleaving in the GNSS message, terminal speed, and satellite elevation angle. Extensive simulations are conducted on BDS-3 B1C B-CNAV1 message and GALILEO E5a F/NAV message. The results validate the excellent error correcting performance of the nonbinary low density parity check (NB-LDPC) code of the B-CNAV1 message and the effectiveness of interleaving in both of the messages in urban condition. Furthermore, it also shows that decoding performance improvement can be achieved with higher terminal speed and higher elevation angle in urban scenarios.

This work investigated concatenated coding schemes for Global Navigation Satellite System (GNSS) signals in order to increase their error correction capability in urban environments. In particular, a serial concatenated code that combines an outer Reed–Solomon (RS) code with an inner low-density parity-check (LDPC) code was designed, and the performance was investigated over the land mobile satellite (LMS) channel for characterizing multipath and shadow fading in urban environments. The performance of the proposed concatenated coding scheme was compared to that of a B-CNAV1 message, in which two interleaved 64-ary LDPC codes were employed. The simulation results demonstrate that the proposed concatenated code can obtain a similar error correction performance to the two interleaved 64-ary LDPC codes in both the additive white Gaussian noise (AWGN) and LMS channels at a lower complexity level.

With the widespread application of Global Navigation Satellite Systems (GNSS), spoofing interference has emerged as a major threat to system security due to its high level of concealment. Traditional static learning models face performance degradation issues in long temporal sequences, making it challenging to meet detection needs in dynamic scenarios. To address this, this paper proposes a Long Short-Term Memory (LSTM) model based on an incremental learning mechanism that dynamically integrates multidimensional features, combined with a hierarchical learning rate strategy and ring-buffer mechanism, for detecting spoofing interference in streaming GNSS signals. Furthermore, to improve robustness under non-stationary and dynamic conditions, the proposed framework introduces a residual standardization based on the Median Absolute Deviation (MAD), a Hampel dual-threshold decision mechanism, and a Huber loss function to suppress the influence of outliers. Experimental validation shows that the proposed method continuously optimizes model parameters through incremental learning, effectively overcoming the extrapolation failure of traditional static LSTM models in ultra-long sequence scenarios. The detection response time is reduced to the millisecond level (7.93 ms), with an accuracy exceeding 98%. Additionally, validation using both simulated Doppler signals and the TEXBAT dataset demonstrates that the method not only achieves high accuracy but also exhibits strong robustness in complex dynamic spoofing scenarios, providing a lightweight and efficient solution for GNSS anti-interference technology.

To avoid signal interference in L1 frequency and provide various services, GPS has updated a modern signal, called L1C, which has been tested with three QZSS satellites launched in 2017. In December 2018, the first GPS III satellite was launched, which implies improved joint positioning using GPS and QZSS L1C signal. The L1C signal offers a series of advanced designs in signal modulation, message structure and coding. We present complete methodologies for joint L1C signal receiving and processing. For the transmitted signals, we present a methodology and results from collecting and assessing Binary Offset Carrier (BOC) modulation and time-multiplexed BOC (TMBOC) modulation used in the L1C signal. Using the same omnidirectional antenna and test equipment, we collected the L1C signal in Xi’an and Sanya, China, respectively. The experiments in Xi’an verify the joint positioning method to complement the GPS III and QZSS satellite constellations. Our methodology evaluates the ranging difference and positioning error of BOC and TMBOC modulation under the same environment and satellite constellation configuration in Sanya. It is also verified that the joint positioning error is less than the QZSS-only positioning due to the optimization of the satellite constellation.

With the development of global navigation satellite systems (GNSS), multiple signals modulated on different sub-carriers are needed to provide various services and to ensure compatibility with previous signals. As an effective method to provide diversified signals without introducing the nonlinear distortion of High Power Amplifier (HPA), the multi-carrier constant envelope multiplexing is widely used in satellite navigation systems. However, the previous method does not consider the influence of sub-carrier frequency constraint on the multiplexing signal, which may lead to signal power leakage. By determining the signal states probability according to the sub-carrier frequency constraint and solving the orthogonal bases according to the homogeneous equations, this article proposed multi-carrier constant envelope multiplexing methods based on probability and homogeneous equations. The analysis results show that the methods can multiplex multi-carrier signals without power leakage, thereby reducing the impact on signal ranging performance. Meanwhile, the methods could reduce the computation complexity. In the case of three different carriers multiplexing, the number of optimization equations is reduced by nearly 66%.