New Algorithm Corrects Time-Varying Polarization Errors

The study addresses a challenge in dual-channel polarization diversity reception systems where mechanical antenna vibration, local oscillator drift, and gain fluctuations cause temporal variations in amplitude and phase errors. These temporal variations lead to the distortion of polarization characteristics. The proposed method, termed TPAF, represents a two-stage approach aimed at stabilizing polarization fingerprints and separating transient noise from the underlying signal.

The authors, including Zhiyuan Ma, Zisen Qi, Hua Xu, and Yunhao Shi, constructed a time-varying amplitude and phase error model specifically for dual-channel systems. To overcome this, they designed a joint blind equalization model in the polarization domain.

The first stage of the TPAF algorithm involves variable-step-size polarization amplitude-phase momentum adaptive filtering, abbreviated as VPM-NLMS. This component dynamically adjusts the iteration step size based on two key metrics: phase concentration and amplitude variance. Additionally, a momentum mechanism is introduced to accelerate transient convergence. This stage is designed to achieve preliminary noise reduction and bias correction of the polarization sequence, preparing the data for more detailed reconstruction in the subsequent phase.

The second stage employs a multi-constraint polarization correction autoencoder, known as PC-AE, for feature reconstruction. This stage utilizes a convolutional encoder-decoder architecture to process the polarization data. A specific polarization amplitude-phase correction loss function is proposed to guide the training of this autoencoder. The loss function combines three distinct components: reconstruction loss, temporal smoothing loss, and phase concentration loss. This multi-constraint approach aims to stabilize the polarization fingerprint while effectively separating transient noise.

Simulation results demonstrate that the proposed method can theoretically effectively suppress time-varying channel disturbances. The study reports that the algorithm significantly reduces estimation errors in both polarization amplitude and phase.

Real-world data results further indicate that the algorithm exhibits a marked improvement over existing adaptive filtering algorithms. The authors state that these practical results fully validate the reliability and practical value of the proposed method.

Subject of Research: Adaptive polarization correction algorithm for dual-channel systems

Article Title: An adaptive polarization correction algorithm for mitigating time-varying amplitude and phase errors

Article References: Ma, Z., Qi, Z., Xu, H., & Shi, Y. (2026). An adaptive polarization correction algorithm for mitigating time-varying amplitude and phase errors. Scientific Reports. https://doi.org/10.1038/s41598-026-76987-8

Image Credits: AI Generated

DOI: 10.1038/s41598-026-76987-8

Keywords: polarization diversity, adaptive filtering, signal processing, TPAF algorithm, phase error correction, amplitude error mitigation, autoencoder, dual-channel systems, blind equalization, Scientific Reports, adaptive, polarization