Antenna arrays with adaptive filtering can protect the integrity and functionality of global navigation satellite system (GNSS) receivers against interference. However, a major problem with existing adaptive array processing algorithms is that they cause phase distortions and introduce bias errors into the carrier phase measurement, limiting high-precision applications. In this paper, a robust phase compensation technique is proposed to reduce the phase distortion. First, a phase bias detection method is developed to trigger the phase compensation technique. Then, the phase bias is estimated using a robust estimation method and compensated for in the GNSS receiver. The proposed technique operates in real time and causes no processing delay, while requiring only a minor modification to existing GNSS receivers. This technique is applied to the power inversion adaptive antenna, and can also be extended to a wide variety of adaptive antennas. The simulation experiments verify the applicability of the proposed technique and also confirm its superiority over existing techniques.

Signal anti-jamming has always been a difficult problem in GNSS (global navigation satellite system) signal processing. There are many GNSS anti-jamming techniques in the existing research, which can achieve good results if the interferences are sparsely distinguishable in some signal feature domains. Specifically, the single antenna based anti-jamming techniques cannot deal with wideband Gaussian noise interference because it is not sparse in time or frequency domain, while the only effective method currently is using multiple antennas to apply the space array processing (SAP) technique since the wideband Gaussian noise interference is sparse in the spatial domain. However, when the incoming directions of the different interferences are not less than that of antennas, the interferences are not sparse to the array anymore, and the SAP anti-jamming performance would decrease drastically. In this paper, a LSTM (long short-term memory) deep neural network (DNN) based algorithm is proposed to enhance the array anti-jamming performance in this situation. The proposed network estimates the interferences as an integrity by exploring the non-linear relationship of the array data received by antennas. Especially, a new loss function is designed exclusively for GNSS anti-jamming problem. The proposed DNN method is verified in the simulation that two wideband Gaussian interferences with JSR (jamming to signal ratio) 50 dB can be eliminated by using two antennas’ data, and the interference cancellation ratio improvement is about 24 dB compared to some other widely used classical SAP algorithms.

The adaptive beamforming algorithm can realize interference suppression and navigation signal enhancement, and has been widely used. However, achieving high-precision real-time estimation of the direction of arrival (DOA) parameters of navigation signals in strong-interference scenarios with low complexity is still a challenge. In this paper, a blind adaptive beamforming algorithm for a Global Navigation Satellite System (GNSS) array receiver based on direction lock loop is proposed without using the prior information of the DOA parameter. The direction lock loop is used for DOA tracking and estimation after interference suppression, which uses the spatial correlation of the array beam pattern to construct a closed direction-tracking loop. The DOA estimation value is adjusted in real time based on the loop errors. A blind beamformer is constructed using the DOA estimation results to provide gain by forming a beam in the satellite direction. This method improves the accuracy and dynamic adaptability of DOA estimation while significantly reducing the computational complexity. The theoretical analysis and simulation results verify the effectiveness of the proposed algorithm.

The time of a satellite navigation system is primarily generated by the main control station of the ground system. Consequently, when ground stations fail, there is a risk to the continuous provision of time services to the equipment and users. Furthermore, the anticipated launch of additional satellites will further strain the satellite–ground link. Next-generation satellite navigation systems will rely on time deviation measurements from inter-satellite links to independently establish and maintain a space-based time reference, enhancing the system’s reliability and robustness. The increasing number of low-Earth-orbit satellite navigation constellations provides ample resources for establishing a space-based time reference. However, this also introduces challenges, including extensive time scale computations, increased link noise, and low clock resource utilization. To address these issues, this paper proposes a Distributed Kalman Plus Weight (D-KPW) algorithm, which combines the benefits of Kalman filtering and the weighted average algorithm, balancing the performance with computational resources. Furthermore, an adaptive clock control algorithm, D-KPW (Control), is developed to account for both the short-term and long-term frequency stability of the time reference. The experimental results demonstrate that the frequency stability of the time reference established by the D-KPW (Control) algorithm reaches $7.40\times {10}^{-15}$ and $2.30\times {10}^{-15}$ for sampling intervals of 1000 s and 1,000,000 s, respectively, outperforming traditional algorithms such as ALGOS. The 20-day prediction error of the time reference is 1.55 ns. Compared to traditional algorithms such as AT1, ALGOS, Kalman, and D-KPW, the accuracy improves by 65%, 65%, 66%, and 67%, respectively.

Deep space exploration utilizing high-orbit vehicles is a vital approach for extending beyond near-Earth space, with orbit information serving as the foundation for all functional capabilities. The performance of orbit determination is primarily influenced by observation types, errors, geometrical structures, and physical perturbations. Currently, research on orbit determination for high-orbit spacecraft predominantly focuses on single observation methods, error characteristics, multi-source fusion techniques, and algorithms. However, these approaches often suffer from low observation accuracy and increased costs. This paper advocates for the comprehensive utilization of existing multi-source observation methods, such as GNSS (Global Navigation Satellite System), SLR (Satellite Laser Ranging), and VLBI (Very Long Baseline Interferometry), in research. The decoupled Kalman filter reveals a positive correlation between measurement positioning accuracy and orbit determination accuracy, and it derives a simple orbit performance evaluation model that considers the influence of observation value types and geometric configurations, without the need to introduce complex dynamic models. Simulations are then employed to verify and analyze antenna gain, observation values, and performance evaluation. The results indicate the following: (1) Under simulated conditions, the optimal strategy involves employing the SLR/VLBI dual system during periods when VLBI orbit determination is feasible, yielding an average Weighted Position Dilution of Precision (WPDOP) of 26.79. (2) For periods when VLBI orbit determination is not feasible, the optimal approach is to utilize the GNSS/SLR/VLBI triple system, resulting in an average WPDOP of 16.32. (3) The orbit determination performance of the triple system is not significantly impacted by the use of global SLR stations compared to using only Chinese SLR stations. However, the global network enables continuous, round-the-clock orbit determination capabilities.

In order to analyze the anti-spoofing performance of the Global Navigation Satellite System (GNSS) multi-beam anti-jamming receiver in the presence of direct repeater spoofing, this paper deduces the theoretical formulas of the output real signal and the direct repeater spoofing signal power of the multi-beam anti-jamming receiver using the minimum variance distortionless response (MVDR) algorithm, when the number of snapshots is limited. The influence of the power of the spoofing signal reaching the surface of the antenna array on the output power of the real signal and the spoofing signal is analyzed in detail. The analysis shows that no matter how the power of the direct repeater spoofing signal is set, the multi-beam anti-jamming receiver using the MVDR algorithm can always suppress the spoofing below the real signal power level, and the suppression effect is more significant when the spoofing signal-to-noise ratio is high. Finally, the correctness of the conclusion is verified by simulation.