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From Simulation to Semi-Physical Validation: An Intelligent Jammer-Assisted Radar Anti-Jamming Evolution Method
Feng Xie1, Huanyu Liu1, Jiaming Wang1
1Information Countermeasure Technique Institute, Faculty of Computing, Harbin Institute of Technology, Harbin 150000, China.
Sensors (Basel, Switzerland)
|August 13, 2026
Summary
This study introduces an intelligent jammer-assisted method for radar anti-jamming evolution, using the AlphaZero framework to enhance radar decision-making against intelligent jammers.
Area of Science:
- Radar Systems Engineering
- Artificial Intelligence
- Signal Processing
Background:
- Adaptive waveform decision-making is crucial for radar anti-jamming against evolving intelligent jammers.
- Current methods face challenges in dynamic adversarial environments.
Purpose of the Study:
- To develop an intelligent jammer-assisted radar anti-jamming evolution method.
- To enhance radar agent's decision-making capability through adversarial interactions.
Main Methods:
- Modeling radar and jammer as competing agents in a sequential decision-making game.
- Utilizing the AlphaZero framework with self-play learning and Monte Carlo Tree Search.
- Implementing a semi-physical hardware-in-the-loop validation platform.
Main Results:
- Accelerated convergence of the radar agent's anti-jamming strategy.
- Improved utilization efficiency of valuable interaction samples.
- Demonstrated practical feasibility bridging simulation and implementation.
Conclusions:
- The proposed AlphaZero-based framework effectively enhances radar anti-jamming capabilities.
- The method optimizes radar strategies through intelligent jammer-assisted evolution.
- The validation platform confirms the practical applicability of the approach.
