Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.
The positioning navigation and timing (PNT) architecture was discussed in detail, whose history, evolvement, current status and future plan were presented, main technologies were listed, advantages and limitations of most technologies were compared, novel approaches were introduced, and future capacities were sketched. The concept of cyber-physical system (CPS) was described and their primary features were interpreted. Then the three-layer architecture of CPS was illustrated. Next CPS requirements on PNT services were analyzed, including requirements on position reference and time reference, requirements on temporal-spatial error monitor, requirements on dynamic services, real-time services, autonomous services, security services and standard services. Finally challenges faced by PNT applications in CPS were concluded. The conclusion was expected to facilitate PNT applications in CPS, and furthermore to provide references to the design and implementation of both architectures.