The current research on the global navigation satellite system (GNSS) has shifted to focus on providing secure and reliable services, rather than high-precision positioning services. Deception jamming has emerged as a major threat to GNSS security applications due to its advantages such as concealment. For security signals not publicly available in the spread spectrum code sequence, simple deception methods do not suffice to implement effective deception. In response, the security code estimation and replay (SCER) attack was proposed. However, the impact of the spread spectrum code estimation error on the receiver and SCER attack effect is still unclear. This paper is based on the SCER attack and deception signal receiving model, constructs a receiver tracking loop analysis model and carrier to noise ratio (CNR) estimation model based on spread spectrum code error, and analyzes the impact of spread spectrum code error on the receiver tracking loop and CNR. Based on the experimental results and discussion, some conclusions have been drawn. Firstly, spread spectrum code error will cause correlation peak distortion and a decrease in CNR. Secondly, to achieve effective deception, the spread spectrum code error cannot be increased indefinitely and an upper bound exists, which ranges from about 41%, depending on the deceived receiver acquisition strategy. Thirdly, when the spread spectrum code error rate is less than the upper bound, the mean square error of the code phase measurement is less than 0.02 chip, which is on the same order of magnitude as caused by thermal noise. As such, it can be approximately assumed that the code tracking deviation caused by spread spectrum code error has minimal impact on the SCER attack. Although reducing the receiving terminal gain of the SCER attack will lead to an increase in the spread spectrum code estimation error, it is possible to increase the transmitting terminal gain of the SCER attack to maintain the same CNR of the deception signal and deception effect, greatly reducing the cost of the deception.

The Global Navigation Satellite System (GNSS) has been applied to all aspects of social livelihood and military applications and has become an important part of national infrastructure construction. However, due to the vulnerability of GNSS, satellite navigation jamming technology can pose a serious threat to GNSS security applications, and this has become a research hotspot in the field of navigation countermeasures. In this paper, satellite navigation jamming technologies are divided into suppression jamming and deception jamming, and the research status of satellite navigation suppression jamming and deception jamming technologies are sorted by three aspects: jamming technology classification, jamming efficiency evaluation, and jamming source deployment. Finally, the future development trend of satellite navigation jamming technology is summarized.

Delay/disruption tolerant network (DTN), in which the network connectivity is intermittent and the node buffer size is limited, is a promising approach to model space networks. In this study, the authors focus on the space deterministic DTNs whose mobility and connectivity are predictable. A rate adaptation scheme based on adaptive modulation and coding (AMC) is adopted. Based on the analysis of data delay in DTN, the authors propose two routing algorithms, namely local information‐based routing (LIR) and local and neighbour information‐based routing (LNIR) for space DTNs. Queuing information in partial nodes is used in routing selection. The two proposed algorithms outperform the traditional least delay routing (LDR) in average end‐to‐end delay, packet loss ratio and traffic distribution. With the same network load, the average delay of LDR, LIR and LNIR are 44.43s, 22.82s and 14.08s while the packet loss ratio of three algorithms are 6.37, 0.76 and 0.00%. Simulation result also shows the superiority of AMC over fixed modulation and coding (FMC) in space DTNs. When the DTN is heavily loaded, the delay of AMC is 15 s smaller than that of FMC. At the same time, the packet loss ratio of AMC is one‐sixth that of FMC.

The pseudolite system can be used to provide positioning and timing service for users in a specific area. In order to provide better positioning and timing service, a good geometric configuration needs to be formed for the pseudolite system. For the problem of pseudolite system deployment, the average and mean square values of geometric dilution of precision (GDOP) are optimized in this paper for users in a target area. We proposed a space-based pseudolite deployment method based on GDOP geometry, starting from the minimum GDOP value for users in the central area. From the simulation results, it can be seen that, compared with the empirical method and the NSGA-II method, the method in this paper has the smallest average GDOP, a better robustness, and a higher positioning accuracy in the target area, through which a pseudolite deployment proposal can be quickly obtained.

When a pseudolite is used to provide positioning services to users, it needs to provide position information by broadcasting ephemeris parameters. As part of resilient positioning, navigation, and timing (PNT), a UAV pseudolite system can serve users independently as a GNSS backup system, but unlike satellites that move periodically, the motion of UAVs is often variable, so it brings difficulties for how to make accurate predictions of the UAV's trajectory in a future segment within the ephemeris parameter update period. Therefore, based on a cruise UAV, we proposed an ephemeris based on a prediction method combined with Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) networks. The true position is divided into positions on the intended route and their deviations by mapping, and we use the motion model, the Singer model with Kalman filter and the CNN-LSTM networks to predict the position. Moreover, the network updates are achieved by a network monitoring loop and adaptive adjustment of the parameter update period is achieved by a prediction accuracy monitoring loop. Moreover, the ephemeris parameters are obtained by fitting the prediction results. The experimental results verify the performance of the designed ephemeris, the root mean squared error (RMSE) value of ephemeris parameter characterization error is less than 5 m, and the average occupied bits is about 35 bits; even using the sample data of UAV maneuvering at extreme speed with poor control performance, the RMSE of ephemeris parameter characterization error is 6.56 m, and the average occupied bits is 69.0 bits.