AI-based Satellite Ground Communication System with Intelligent Antenna Pointing

With the advent of the Internet era, the trend of highly informed society has been becoming more and more obvious, and the requirement of society on communication is also increasing. flexible satellite communication mode has many advantages such as large communication load and no geographic restriction, which cannot be replaced by other communication modes. In the satellite communication system, the most important is the satellite earth station (SES). When receiving signals from the target satellite, the SES terminal must accurately point to the satellite and track it to obtain the maximum receiving signal and reduce the interference with other signals simultaneously. However, the motion of either satellite or terminal can cause a change in signal intensity, so it is necessary to adjust the pointing of the SES antenna in time to maintain optimal signal receiving conditions. In order to satisfy different satellite communication scenarios, in this paper, Artificial intelligent (AI) technology is applied to the satellite communication process, mainly to optimize the optimal antenna angle and time consumption reduction. Firstly, the process of antenna pointing is introduced, and the traditional antenna search algorithm Auto-Acqire algorithm (AA algorithm) is analyzed in detail. Considering that the satellite system needs to adapt to the communication requirements of different terminals, based on AI antenna pointing algorithms are proposed. In order to verify this research, we build an experimental platform and compare the traditional AA algorithm as a benchmark algorithm with FI-GRU and II-DRL algorithms. According to the experimental results, the two algorithms proposed in this paper can improve the efficiency of satellite pointing and tracking tasks.