Spoofing interference poses a significant challenge to the Global Navigation Satellite System (GNSS). To effectively combat intermediate spoofing signals, this paper presents an enhanced spoofing detection method based on abnormal energy of the quadrature (Q) channel correlators. The detailed principle of this detection method is introduced based on the received signal model under spoofing attack. The normalization parameter used in this method was the estimation of the noise floor. The performance of the proposed Q energy detector is validated through simulations, the Texas Spoofing Test Battery dataset and field tests. The results demonstrate that the proposed detector significantly enhances detection performance compared to signal quality monitoring methods, particularly in overpowered scenarios and dynamic scenarios. By increasing the detection probability in the presence of spoofing signals and decreasing the false alarm probability in the absence of spoofing signals, the proposed detector can better meet the requirements of practical applications.

Owing to the existence of non‐line‐of‐sight (NLOS) signals in global navigation satellite system (GNSS) challenged environment, the real‐time kinematic (RTK) position precision is seriously damaged. In order to improve the position accuracy, the authors propose a robust positioning method which tackles this problem by detecting the NLOS through a decision tree and estimating the double‐differenced multipath errors in real time. The NLOS detection performance of the proposed method is 95.64%. The field experiment shows that the ambiguity fixing rate has improved by 43% in the instantaneous mode, and the 3D position accuracy is about 81.77% higher better than that of normal RTK method which is implemented by using RTKLIB software.

Adaptive antenna arrays are widely used to protect Global Navigation Satellite System (GNSS) receivers from interference. However, conventional blind anti-jamming array processing methods can cause satellite signal attenuation, which reduces signal tracking precision and measurement accuracy. To alleviate this problem, this paper proposes the noncoherent channel combining method for GNSS signal tracking with an adaptive antenna array. A two-stage processing architecture is applied in the proposed method, where the first stage implements interference suppression, and the second stage achieves noncoherent channel combining. The proposed method has the advantage of blind characteristics that can be implemented without any other auxiliary information. It also reveals a unified processing architecture for anti-jamming array processing methods. Thus, a detailed comparison and analysis of the proposed method with several typical blind anti-jamming methods is performed. Simulation results demonstrate the effectiveness of the proposed method and its superiority over existing methods in terms of tracking performance.

Zero bias is the main source of error in high‐precision applications based on pseudo‐noise (PN) ranging. This study proposes a selective non‐commensurate sampling frequency design method applied to the digital code‐tracking loop which can effectively suppress the code‐phase zero bias caused by incomplete sampling of the spread spectrum signal. The maximum (MAX) and standard deviation (STD) of the zero bias independent of code and the initial phase are used to design the sampling frequency. The code correlation reference waveform is utilised to establish a statistical analysis model of the digital discriminator zero bias. Analytical expressions of the zero‐bias MAX and STD are derived. The performance of the proposed method is assessed as per code Doppler, binary offset modulation, and thermal noise. Fibre optic time synchronisation equipment is used to determine the feasibility of eliminating PN code‐tracking zero bias based on selective non‐commensurate sampling.

In time synchronisation systems, the code phase of the spread spectrum signal is an important characteristic that can provide users with high‐precision and unambiguous observation results. However, digital code phase discriminators have limited sampling frequencies that distort the signal correlation peak and generates a zero‐bias code‐phase estimate. In this Letter, the authors evaluate and analyse the zero‐phase deviations of digital code phases. An optimal correlation interval design method, based on a code phase discriminator that can effectively suppress the zero‐crossing deviation, is also proposed. The simulation results show that the proposed algorithm can reduce the deviation of 96.5% and effectively improve the measurement accuracy of the code phase.

In high precision applications based on binary subcarrier offset (BOC) signals, zero-bias of the digital discriminator is an error of importance. Unlike the thermal noise error, zero-bias is a fixed deviation that is challenging to eliminate by filtering in the time domain. In this paper, a statistical error analysis model for the zero-bias of BOC signal’s digital phase discriminator is established. The evaluation of the zero-bias is inseparable from the spreading code sequence and the initial phase of the signal through defining the concept of statistics maximum and statistics standard deviation. Based on the zero-bias statistical error analysis model, two receiver parameter design methods, namely, the baseband signal sampling frequency and the early-late correlation interval, are proposed. The performance of the algorithm is simulated on account of the limited bandwidth, Doppler frequency offset and thermal noise. The simulation results prove that the proposed algorithm can suppress the standard deviation of zero-bias within one phase resolution, which contributes substantially to the improvement of the measurement accuracy of pseudo-noise ranging.