Study On Calculation Method Of Electromagnetic Situation For Radar Countermeasure

With the continuous evolution of the battlefield morphology towards informatization,the electromagnetic spectrum,as a carrier of battlefield information transmission and electronic confrontation,has become increasingly fierce for its control,so the current battlefield situation needs to be expanded to the field of electromagnetic situation.Based on the electromagnetic situation faced by radar countermeasures,this paper conducts research on the electromagnetic situation recognition and related situation knowledge calculation methods for radar countermeasures.The main work includes the following aspects:1.The situational layered cognition method and knowledge representation method of electromagnetic situation for radar countermeasure are proposed.This part first explains the understanding of radar countermeasures.Then,starting from the concept of hierarchical cognition,a hierarchical cognitive model of radar confrontation situation is proposed.Based on the layered cognition of radar countermeasure situation,the knowledge representation method of radar countermeasure situation based on layered cognition is studied to provide a basis for the subsequent research on the calculation method of radar countermeasure situation.2.The method of recognition of deceptive jamming signals in radar countermeasures is studied.Based on the layered cogn ition of radar countermeasures,the first layer of cognition needs to complete the recognition of radar jamming signal patterns.The research content of this part is to apply bispectrum analysis and deep learning to radar interference recognition,and convert interference signal recognition into images for classification recognition.First,bispectrum analysis is performed on the radar deception jamming signal to obtain the bispectrum image,which is used as the input of the convolutional neural network model,the network is trained and recognized,and the deception jamming signal is identified.3.The inference method of enemy target intention in radar confrontation situation is studied.On the basis of the second layer of cognition of radar confrontation situation,it is necessary to complete the reasoning of target intent in radar confrontation.According to the data detected by radar and other equipment,GA-BP neural network is used to train and identify the data,so as to complete the reasoning of the enemy’s target intention in the radar confrontation situation,and design the target intention inference program.4.The method of estimating the threat degree of enemy targets in radar confrontation situation is studied.On the basis of layered cognition of radar confrontation situation,the third layer of cognition needs to complete the estimation of the threat level of enemy targets in radar confrontation.This section is mainly to study how to use dynamic Bayesian network to analyze the threat degree of aerial targets,and use Ge NIE2.0software for system modeling and analysis with simulation cases.