A Cognitive Jamming Decision-making Method for Multi-functional Radar Based on Threat Assessment

Multi-function radar (MFR) plays an important role in modern battlefield, and the cognitive jamming decisionmaking method for MFR is the key technology to effectively interfere MFR, which is of great research significance. In order to effectively interfere MFR, a cognitive jamming decision-making method based on threat assessment is proposed in this paper. Firstly, the problem of jamming decision-making is modeled as a Markov decision process with reward. Creatively, rewards will be given by a track-based threat assessment model, by which the jamming strategies are able to fit the real-time requirements of electronic countermeasures. Finally, the Q-Learning algorithm is used to solve the problem and derive the optimal jamming strategy. Experiment results show that the proposed jamming strategy is more effective in reducing the threat of MFR to the target. Compared with the present methods, the proposed approach has advantages in real-time performance and effectiveness of jamming decision-making, and has more practical value.