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Research on Multi-Feature Fusion and Lightweight Recognition for Radar Compound Jamming.

Weiyu Zha1, Jianyin Cao1, Hao Wang1,2

  • 1School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Sensors (Basel, Switzerland)
|February 27, 2026
PubMed
Summary

This study introduces a lightweight network for recognizing radar compound jamming, achieving over 87% accuracy even in low signal conditions. The efficient model is ideal for electronic counter-countermeasure applications.

Keywords:
lightweight recognitionlow JNRmulti-feature fusionradar compound jamming

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Area of Science:

  • Radar Systems Engineering
  • Artificial Intelligence
  • Signal Processing

Background:

  • Complex electromagnetic environments pose challenges for radar systems due to sophisticated jamming techniques.
  • Accurate recognition of compound jamming is crucial for effective electronic counter-countermeasure (ECCM) operations.

Purpose of the Study:

  • To develop a lightweight, high-accuracy network for recognizing radar compound jamming under challenging conditions.
  • To balance recognition performance with computational complexity for practical ECCM deployment.

Main Methods:

  • Utilized three complementary time-frequency representations for multi-feature extraction of compound jamming.
  • Employed a multi-branch architecture with attention mechanisms for parallel, multi-scale feature learning and enhancement.
  • Integrated features using a weighted fusion strategy and incorporated the lightweight GSENet module.

Main Results:

  • Achieved over 87% recognition accuracy for seven compound jamming types under low jamming-to-noise ratio (JNR) conditions.
  • The proposed network has a low parameter count, below 0.14 million.
  • Demonstrated an effective trade-off between recognition performance and model complexity.

Conclusions:

  • The developed lightweight multi-feature fusion network is effective for radar compound jamming recognition.
  • The network's efficiency and accuracy make it suitable for real-time ECCM applications.
  • The approach offers a viable solution for enhancing radar resilience in complex electromagnetic environments.