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Robust Polarization-Domain Adaptive Anti-Jamming via Forgetting-Factor Covariance Estimation and Adaptive Diagonal
Yuancong Xiong1, Huafeng He1, Buma Xiao1
1College of Missile Engineering, Rocket Force Engineering University, Xi'an 710025, China.
Sensors (Basel, Switzerland)
|July 15, 2026
Summary
This study introduces a novel adaptive anti-jamming framework for dual-polarized radars, enhancing performance with limited data and dynamic interference. The method improves signal quality and jammer suppression using forgetting-factor covariance estimation and adaptive loading.
Area of Science:
- Radar Systems Engineering
- Signal Processing
- Electromagnetics
Background:
- Dual-polarized radars face challenges with jamming, especially with limited data and time-varying interference.
- Existing robust adaptive beamforming methods often require complex parameters or assumptions not always met in real-world scenarios.
Purpose of the Study:
- To develop a robust polarization-domain adaptive anti-jamming framework for dual-polarized radars.
- To address limitations of secondary data availability and time-varying interference.
- To enhance radar performance through improved jammer suppression and signal quality.
Main Methods:
- Proposed a covariance-reliability-driven Minimum Variance Distortionless Response (MVDR) framework.
- Implemented forgetting-factor covariance estimation to prioritize recent data for nonstationary interference.
- Utilized adaptive diagonal loading controlled by sample deficiency and covariance condition number for stability.
Main Results:
- Achieved competitive output Signal-to-Interference-plus-Noise Ratio (SINR).
- Demonstrated effective jammer suppression capabilities.
- Showcased improved robustness against moderate Direction of Arrival (DOA) and polarization mismatches.
- Validated performance under limited-snapshot and time-varying interference conditions.
Conclusions:
- The proposed MVDR framework offers a robust solution for dual-polarized radar anti-jamming with limited data.
- The method effectively handles nonstationary interference and improves system stability.
- Further validation with real-world radar data is recommended.
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