# Low Signal-to-Noise Ratio Optoelectronic Signal Reconstruction Based on Zero-Phase Multi-Stage Collaborative Filtering

**Authors:** Xuzhao Yang, Hui Tian, Fan Wang, Jinping Ni, Rui Chen

PMC · DOI: 10.3390/s25092758 · Sensors (Basel, Switzerland) · 2025-04-27

## TL;DR

This paper introduces a new signal processing method to improve detection accuracy in low signal-to-noise environments for laser-based systems.

## Contribution

A novel multi-stage collaborative filtering framework with zero-phase FIR filtering and wavelet-based reconstruction is proposed.

## Key findings

- The method achieves a 25 dB SNR improvement under −20 dB conditions.
- Processing time is reduced from 0.42 to 0.04 seconds.
- Boundary artifacts are effectively suppressed in low SNR scenarios.

## Abstract

The Laser Light Screen System faces critical technical challenges in high-speed, long-range target detection: when a target passes through the light screen, weak light flux variations lead to significantly degraded signal-to-noise ratios (SNRs). Traditional signal processing algorithms fail to effectively suppress phase distortion and boundary effects under extremely low SNR conditions, creating a technical bottleneck that severely constrains system detection performance. To address this problem, this paper proposes a Multi-stage Collaborative Filtering Chain (MCFC) signal processing framework incorporating three key innovations: (1) the design of zero-phase FIR bandpass filtering with forward–backward processing and dynamic phase compensation mechanisms to effectively suppress phase distortion; (2) the implementation of a four-stage cascaded collaborative filtering strategy, combining adaptive sampling and anti-aliasing techniques to significantly enhance signal quality; and (3) the development of a multi-scale adaptive transform algorithm based on fourth-order Daubechies wavelets to achieve high-precision signal reconstruction. The experimental results demonstrate that under −20 dB conditions, the method achieves a 25 dB SNR improvement and boundary artifact suppression while reducing the processing time from 0.42 to 0.04 s. These results validate the proposed method’s effectiveness in high-speed target detection under low SNR conditions.

## Full-text entities

- **Diseases:** injury to (MESH:D014947), MCFC (MESH:D062706)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

19 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12074170/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/PMC12074170/full.md

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Source: https://tomesphere.com/paper/PMC12074170