August 15, 2025Applied SciencesOpen Access

Dynamic Jamming Policy Generation for Netted Radars Using Hybrid Policy Network

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Proposed method optimizes jamming resource allocation for radars, reducing power usage and enhancing performance against threats.

The proposed method achieves robust jamming performance against eavesdroppers while minimizing resource consumption.
Experiments show superior convergence speed with reduced power consumption compared to baseline methods.
The framework utilizes deep reinforcement learning to optimize resource allocation strategies for adaptive jamming.
A hybrid policy network dynamically coordinates beam selection and power allocation in complex electromagnetic environments.

Hao et al. (2025) studied this question.

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August 15, 2025Applied SciencesOpen Access

View Full Paper

Ask AI

Bookmark

Authors

Proposed method optimizes jamming resource allocation for radars, reducing power usage and enhancing performance against threats.

The proposed method achieves robust jamming performance against eavesdroppers while minimizing resource consumption.
Experiments show superior convergence speed with reduced power consumption compared to baseline methods.
The framework utilizes deep reinforcement learning to optimize resource allocation strategies for adaptive jamming.
A hybrid policy network dynamically coordinates beam selection and power allocation in complex electromagnetic environments.

Hao et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark