Modeling And Interference Analysis Of XXX Ship XXX Communication Systems

In the new international situation, the xxxx is playing a more and more important role in China’s military strength. The situation in which xxxx ships work as formation to undertake tasks will be more and more popular. Therefore, the guarantee of telecommunication safety during all kinds of tasks is becoming very important. However, due to the fact that there are lots of communication systems on the vessels, including radar, data link, navigation and satellite, and the fact that lots of these systems operate in adjacent channels, it has become an urgent demand to guarantee the coexistence of all these communication systems when working in neighbored area and adjacent channels.To solve the problem mentioned above, this paper provided an integrated solution for the telecommunication safety of xxx formation. Major tasks and innovations include:1) Conducting interference analysis and modeling of the communication systems on the vessels. Deterministic analysis and link level simulation of the coexistence of radar and datalink are made to provide criteria for them to operate normally in neighbored area and adjacent channels.2) The signal recognition solution based on the spectrum template is provided. The spectrum templates are constructed for both known signals and unknown signals. The fast signal recognition is achieved by comparing the spectrum template of both known and unknown signals. Besides, experiments are also made to testify the effectiveness of this solution.3) According to the demands of xx formation when executing tasks on the ocean, the spectrum presentation platform is designed and developed, through which the function of storing system information, presenting spectrum situation and showing the spectrum occupation are realized. This could be regarded as a realistic exploration of utilizing spectrum situation in the scenario where xx formation executes tasks in the ocean.The work mentioned above was utilized in the enterprise project. In the future, we hope to bring in new techniques such as machine learning and3-D spectrum situation to further ameliorating these research accomplishments.