Research On SAR Jamming Decision Method Based On Game Theory

Synthetic Aperture Radar(SAR)has the advantages of all-time,all-weather,long range and high imaging resolution.It is used in marine resource detection,natural disaster prevention,terrain surveying and other civilian fields,as well as combat effect evaluation,battlefield situation reconnaissance,etc.Weapon and equipment guidance and other military fields have played an important role.When we use SAR for reconnaissance and imaging,the enemy is also using SAR to observe our important targets and scenes.Therefore,formulating reasonable SAR interference decision-making methods is of great significance to protecting our targets.Due to the complex SAR countermeasure scenarios and various interference patterns,how to quickly determine the most appropriate interference pattern is an important research direction for SAR countermeasures,and it is of great significance to improve the effectiveness of one's own interference.Game is a process in which one or more rational actors take actions and obtain corresponding benefits.SAR confrontation is a typical game,and it is difficult for the interfering party to directly obtain accurate jamming images,SAR anti-jamming styles and jamming effects during the game.As a result of the evaluation,the information of the jammer is lacking.The jammer has some considerable information about the battle,and it is difficult to make reasonable jamming decisions.Therefore,a Partially Observed Markov Decision Process(POMDP)is used to describe SAR countermeasures and study SAR based on game theory.The interference decision method has important theoretical significance and application value.Based on SAR imaging principles,SAR typical interference and anti-jamming mechanism,this paper designs SAR interference effect evaluation methods,and uses this as a decision-making basis to establish a SAR dynamic game model that fits actual combat scenarios,and in-depth study of SAR interference decision methods to improve SAR interference Real-time and accuracy of decision-making.The main achievements and innovations of this thesis are as follows:1.The basic principles of SAR imaging and SAR typical interference and anti-jamming mechanism are introduced in detail,which provides a theoretical and technical basis for the follow-up study of SAR interference effect evaluation criteria and interference decision generation methods.First,the SAR imaging geometric model is established,and the rangeDoppler method of the SAR classic imaging algorithm is introduced and simulated.Secondly,from the perspective of active and passive anti-jamming,SAR anti-jamming principles such as frequency domain notch,time-frequency domain filtering,frequency hopping and interpulse modulation frequency agility are discussed in detail.Then,according to the coherence of the jamming signal and the SAR signal,the SAR jamming methods such as suppression jamming,semi-matching jamming and deception jamming are introduced in detail.Finally,in view of the single and low accuracy of the traditional SAR game model,Partially Observed Markov Decision Process(POMDP)is used to describe the SAR dynamic game process.2.In order to solve the problems that the existing jamming decision making depends on experts' subjective judgment or predetermined jamming decision making conditions,and the existing jamming effect evaluation model is difficult to accurately describe the wartime countermeasure effectiveness,a multi-dimensional jamming effect evaluation method is proposed in this thesis.Accurate and reasonable jamming effect evaluation results are the key for the jammers to make correct decisions.Therefore,considering the non-equivalence of information between the two sides of the SAR countermeasure in the actual combat scenes,this thesis designs the jamming effect evaluation methods from the SAR side and the jammers respectively: jamming effect evaluation method based on image quality of the SAR side;Based on the change characteristics of time domain,frequency domain,space domain and power domain,combined with the jamming effect evaluation method of SAR antijamming style recognition and jamming evaluation hierarchical structure model,the jamming effect evaluation results were taken as the jamming decision criteria.Finally,the effectiveness of the jamming effect evaluation method is verified by the simulation experiment of SAR countermeasures.3.Aiming at the problem that the traditional SAR game model is difficult to accurately represent the SAR dynamic game process and the traditional game solution method has limitations,POMDP is used to describe the SAR dynamic game process,and the Markov Decision Process(MDP)is based on POMDP.The SAR dynamic game model is used to accurately characterize the SAR countermeasure scene,and the belief space is introduced to reduce the dimensionality of the interference decision space.Then,starting from the value iteration algorithm,a SAR jamming decision method based on the Q-Learning algorithm and the Sarsa algorithm is proposed to solve the SAR countermeasure dynamic game problem under incomplete information,and the difference between the two algorithms in the strategy update method is analyzed in detail.Finally,the performance of different algorithms is compared and analyzed through simulation verification,which verifies the effectiveness of the algorithm proposed in this thesis.