Research On Interference Perception Based On Knowledge Graph

In the informationized battlefield,interference perception plays an important role in the evaluation and management of the electromagnetic spectrum,and is a crucial guarantee for the normal operation and efficient transmission of communication systems.However,in the current electromagnetic environment,various interference information does not exist in isolation but has close and complex relationships.The structured features of Knowledge Graph(KG)can well depict such an environment and analyze and reason based on the relationships between interference information,providing new technologies and methods for research on electromagnetic interference perception.Therefore,based on knowledge graphs,the thesis conducts research on the identification of jamming devices and the evaluation of jamming threats from two aspects.The main contents and contributions are as follows:Firstly,to address the problem of how to represent the relationships among various interference sources and their parameters in complex electromagnetic environments,we propose the concept and construction method of interference knowledge graph.We represent the entities,attributes,and relationships of interference source information using the web ontology language and construct the ontology model using a seven-step method.Based on this,we provide a construction method for the interference knowledge graph.We store the interference knowledge graph using the Neo4 j database and achieve efficient query of the historical parameters of interference sources through Neo4 j.Next,a method for efficient identification of interfering devices based on knowledge graph was proposed.The interference information triple knowledge was transformed into embedding vectors using the TransD model,and feature enhancement was performed using multi-head self-attention mechanism and Convolutional Neural Networks(CNN).Interference device identification was achieved through similarity matching.Simulation experiments showed that the proposed algorithm has a fast convergence speed and high recognition accuracy under complete and missing data,and can effectively realize realtime perception of interference devices.In addition,based on the proposed algorithm and model,a simulation software for interference device identification based on knowledge graph was developed and its functionality was demonstrated using GUI.Finally,addressing the issue of threat level assessment of interference devices,a knowledge graph-based interference threat assessment algorithm is proposed.An assessment model for interference threat is designed,and the TransD model is used to embed entities and relationships in interference information into knowledge vectors.The interference threat level is evaluated using a multi-layer perceptron model.Simulation experiments show that the proposed algorithm can effectively evaluate interference threat levels.