A Cognitive Electronic Attack Evaluation Method Based on Behavior Recognition

In order to improve the effectiveness of cognitive electronic attack, this paper proposes a novel method to evaluate the effectiveness of cognitive electronic attack based on behavior recognition. In the modern battlefield environment, the electronic attacker establishes the behavior observation space of the target and its collaborator, and obtains their behavior parameters. These behavior parameters are closely related to the effect of electronic attack. A trained neural network being used to identify and process the behaviors of the target and its collaborator, the evaluation value of the electronic attack effect obtained by this method can achieve much higher accuracy than the traditional method. The application of the evaluation results can provide the necessary information for the OODA loop attack strategy and speed up the OODA loop.