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Targeted Antibody Blocking by a Dual-Functional Conjugate of Antigenic Peptide and Fc-III Mimetics (DCAF)

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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.

Keywords:

adaptive beamforming anti-jamming covariance estimation diagonal loading forgetting factor polarization-domain radar robust MVDR

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Targeted Antibody Blocking by a Dual-Functional Conjugate of Antigenic Peptide and Fc-III Mimetics (DCAF)

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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

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Published on: January 14, 2020

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.