Knowledge-based Research On Radar Jamming Decision-making

Since the invention of radar,many researchers have devoted themselves to improving the performance of radar.With the continuous deepening of research in the field of electromagnetics,modern warfare has gradually transformed into a battle in the field of electromagnetics,and the role of radar is becoming more and more significant.Likewise,jamming the radar to prevent it from working properly has become an important part of the electronic countermeasures process.Most of the traditional jamming is based on the analysis of real-time received radar data combined with the jamming strategy library to make jamming decisions.This data-driven jamming decision-making algorithm has high data requirements and has effective interference when radar equipment uses the parameters that have been recorded.However,in the process of confrontation,there is still a lot of prior knowledge information,and radar equipment often uses some new parameter combinations.How to introduce knowledge information into the interference decision-making process in this case has important research significance.In this thesis,the prior knowledge information in the confrontation process is analyzed,and certain mathematical models are combined to realize the combination of knowledge information and radar jamming decision-making process.The main work and contributions of this thesis include the following three aspects:Firstly,based on the mathematical model of the radar echo signal,the processing process of the radar received signal and the radar jamming signal model are studied.Based on chirp signal,the radar echo signal model is analyzed.The pulse compression and moving target processing methods in the radar receiving and processing process are studied,and the signal waveform after processing is analyzed by simulation.Then,the mathematical modeling of noise amplitude modulation,noise frequency modulation signal in suppressing jamming signal and distance deception,speed deception signal in deceptive jamming signal is carried out,and the characteristics of different jamming signals are analyzed combind with simulation waveforms.Secondly,the modeling and characterization techniques of radar system knowledge and the application of knowledge in radar jamming decision-making are studied.After analyzing the characteristics of radar system knowledge,the knowledge graph and graph embedding algorithm are used to model and represent knowledge information.By introducing Bayesian network and data-knowledge fusion network,the reasoning process of radar equipment and working status is completed.Based on the reasoning results of these two parts and the interference decision-making library,a knowledge-based interference decision-making algorithm is proposed to realize applications of knowledge-information in the decision-making process.Thirdly,an adversarial simulation system is constructed to verify the effectiveness of the interference decision-making method.By modeling the radar's work and the jamming decision of the jammer,combined with the underlying signal model of the radar's receiving and processing,a countermeasure simulation system is constructed.The jamming performance of the knowledge-based radar jamming decision-making method and the data-driven template-matching jamming decision-making method is verified by simulation.The results show that the performances of the two methods is almost the same in the known radar working state.While in the unknown radar working state,the interference performance of knowledge-based jamming decision-making method is improved by an average of 7.61% compared with that of the template-matching interference decision-making method.