一种基于机器学习的卫星重叠隐蔽通信方法

针对传统卫星重叠通信中单个掩护信号带宽以及功率容限不够的问题，利用卫星转发器频谱环境中多个掩护信号提出了一种频域分割-子谱功率控制联合优化的多掩护信号重叠通信方法，建立了隐蔽通信信号传输性能和隐蔽性能的双目标优化问题，信关站侧采用感知的历史频谱数据训练生成支持向量机回归预测模型，用来预测不同转发器频谱环境下隐蔽信号的通信性能和隐蔽性能，并将训练好的预测模型下载到通信终端；终端侧利用双目标背包算法将支持向量机回归预测模型预测的隐蔽信号的通信性能和隐蔽性能作为价值因素、掩护信号个数作为背包重量来选择转发器频谱环境中的掩护信号，并且求解出隐蔽信号的频域分割和子频谱的功率控制参数，从而实现终端通信信号隐藏在卫星转发器的频谱环境中的目的。

A Satellite Covert Overlap Communication Method Based on Machine Learning

? ?Aimed at the problem of insufficient bandwidth and power tolerance of a single cover signal in the traditional satellite overlapping communication， a multi-cover signal overlapping communication method with frequency domain division and sub-spectrum power control joint optimization was proposed by using multiple cover signals in the satellite transponder spectrum environment. A bi-objective optimization problem of signal transmission performance and stealth performance for covert communication was established. The gateway side used the perceived historical spectrum data to train and generate the support vector machine regression prediction model， which was used to predict the communication performance and stealth performance of covert signals in different transponder spectrum environments， and downloaded the trained prediction model to the communication terminal. The terminal side used the dual-target knapsack algorithm to select cover signals in the transponder spectrum environment by taking the communication performance and covert performance of the covert signal predicted by the support vector machine regression prediction model as value factors， and the number of cover signals as the backpack weight， and solved the frequency domain division of the concealed signal and the power control parameters of the sub-spectrum， so as to realize the purpose of hiding the terminal communication signal in the frequency spectrum environment of the satellite transponder. This method not only solves the problem of insufficient power and bandwidth tolerance of single cover signal in traditional covert communication， but also comprehensively optimizes the communication performance and covert performance of covert communication system. Due to the long propagation delay of satellite communication， the advantage of adopting the method proposed in this paper is that the terminal and the gateway station can avoid the interaction between the receiver and the receiver in the communication process by using the same historical database and the machine learning prediction model， and quickly obtain the required covert communication transmission strategy based on the current spectrum environment.