Generation Method Of Communication Anti-jamming Strategy In Complex Confrontation Environment

Hybrid direct Sequence/frequency hopping(DS/FH)communication system has been widely used in anti-jamming communication because of its high spectrum utilization,remarkable anti-interception and anti-jamming performance,which can reduce the influence of artificial interference to a certain extent.With the development of cognitive technology and the continuous upgrading of interference technology,the emergence of cognitive interference technology has led to an increasingly complex electromagnetic environment.It is difficult for the existing DS/FH to meet the requirements of antijamming communication,and the core problem of improving the anti-jamming performance of the DS/FH is how to select the appropriate frequency hopping rate and communication frequency.Aiming at these problems,based on the analysis of the working principle of the hybrid hop-spread communication system,this thesis conducts research on the generation method of communication anti-jamming strategy in complex confrontation environment.The specific work is as follows:1.The generation method of anti-tracking interference strategy based on reinforcement learning is studied.Through the learning ability of the reinforcement algorithm to the environment,the DS/FH can adjust its own working mode according to the environment state,which improves the performance degradation of the current DS/FH in the tracking interference environment,and effectively improve the anti-interference performance of the DS/FH in the complex electromagnetic environment.2.The generation method of anti-adaptive tracking jamming strategy based on reinforcement learning is studied.The bit error rate is used as the communication performance index,and the anti-jamming model with the main goal of reaching the optimal frequency hopping rate is established.The problem of performance degradation of DS/FH in adaptive tracking jamming environment is improved,and the anti-jamming performance of the system in complex countermeasure environment is effectively improved.3.The intelligent frequency selection algorithm based on reinforcement learning is studied.Using the bit error rate as the communication performance index,an antiinterference model with the main goal of selecting the optimal communication frequency band is established.Using this algorithm,DS/FH can avoid the channel with interference,so as to improve the reliability and stability of the system in the complex electromagnetic environment.4.The generation method of anti-cognitive interference strategy based on reinforcement learning is studied.The bit error rate is used as the communication performance index,and an anti-interference model with the main goal of achieving the optimal frequency hopping rate is established.The problem of the decline of the stability of the DS/FH in the cognitive interference environment is improved,and the bit error rate performance of the system in the complex countermeasure environment is effectively improved.