Radar Cognitive Behavior Identification And Jamming Decision Optimization

In the current warfare,the gain of the electromagnetic spectrum advantage is depended to a certain extent on the accuracy of radar reconnaissance and the effectiveness of jamming decision.If the future behavior of the enemy can be predicted according to its behavioral changes in a period of time the initiative of the battlefield can be took.At the same time,if interference system can reasonably allocate resources according to the radar status,then the enemy radar can be interfered in the greatest extent.Based on the above situation,two innovative improvements are proposed in this dissertation.First of all,the radar behavior obtained by the reconnaissance system is used to predict the future radar behavior in real time.Then,finding the balance between the prediction results,interference resource pool and the power of the interference system,so that the interference success rate is relatively largest and the less interference resources are utilized.The main content are as follows:Firstly,specific analysis is made for radar behavior and interference signal classification.Three kinds of common radar behaviors and their characteristics are explained.Then the several typical types of masking and deception jamming are described and their simulation principles are simulated.Secondly,the real-time prediction of radar's future behavior is made by using the recognition results of enemy behavior in a period of time obtained in reconnaissance system.At the beginning,this dissertation defines a way to represent the recognition results and error value of radar state by numbers,and taking the current radar state value and previous radar state value as parameters to predict the future state of the radar.In order to avoid the irrationality of data fluctuation in state transition of traditional Markov process,the belief Markov model is used.This model not only effectively predicts the possibility of radar state transition,but also reflects the predicted error in the final results.Due to the real-time radar behavior recognition in reconnaissance system,the prediction results of radar behavior can also change in real-time.Then,the method is verified and the simulation results show that the method can predict the future behavior of radar in real time according to the radar behavior.Finally,a new jamming decision optimization algorithm is proposed.Based on the jamming side,this dissertation redefines the interference success rate.In jamming decision,the radar behavior state,the jamming pattern and the power allocated to jamming pattern are mutually restricted,so the end condition of the optimization algorithm is to find the balance point of the above three.It is assumed that multiple interference patterns are used for one radar and the objective of decision optimization is to give the allocation values of the power of different jamming patterns for each behavior state of radar.The allocation values are such that the power consumption of jamming pattern is relatively small when the total success rate is relatively high.In order to solve the above multi-optimization problem,the NSGA-III is adopted.At the end,the jamming decision optimization algorithm is simulated and validated by using the radar behavior prediction results which proposed in the previous section of this dissertation.The results show that the algorithm can effectively solve the problem of difficult interference when resources are limited,and realize the optimization of jamming decision.