大数据资源调度下船舶通信网络干扰信息识别研究

Research on interference information identification of ship communication network based on big data resource scheduling

作者单位:

交通运输部 北海航海保障中心 天津通信中心，天津 300456Tianjin Communication Center, Northern Navigation Service Center, Marltime Safety Administration, Tianjin 300456, China

大数据;资源调度;船舶通信网络;干扰信息识别;时频特征;时域特征big data; resource scheduling; ship communication network; interference information recognition; time-frequency characteristics; the time domain characteristics

为了有效识别出船舶通信网络中的干扰信息，针对大数据资源调度下船舶通信网络干扰信息识别方法展开研究。采用数据挖掘方法获取船舶通信网络信息中的干扰信号，依据大数据资源调度获取干扰信息的时频、时域特征，基于奇异值分解算法降低特征维度并完成特征融合，依据改进的Softmax回归模型识别船舶通信网络干扰信息类别。测试结果显示：该方法具备良好的船舶通信网络干扰信息特征提取效果，能够有效识别出通信网络中的5类干扰信息，为船舶的管理和航行监控提供可靠保障。In order to effectively identify the interference information in ship communication network, the identification method of ship communication network interference information under big data resource scheduling is studied. The data mining method is used to obtain the interference signal in the ship communication network information and form the digital communication data information. The time-frequency and time-domain characteristics of the interference information are obtained according to the big data resource scheduling, based on the singular value decomposition of the communication network, the classification algorithm of the communication network is improved, and the interference is reduced. The test results show that this method has good feature extraction effect of ship communication network interference information, reliably identifies five types of interference information in the communication network, and provides a reliable guarantee for ship management and navigation monitoring.

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