Optimization of Jamming Type Selection for Countering Multifunction Radar Based on Generative Adversarial Imitation Learning
In recent years, deep reinforcement learning (DRL) has made some progress in jamming type selection (JTS). However, during the training process of the agent, exploration of the action space is necessary, which leads to poor jamming effects in the early stages of training, posing a significant threat...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10844286/ |
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