Low Signal-to-Noise Ratio Optoelectronic Signal Reconstruction Based on Zero-Phase Multi-Stage Collaborative Filtering
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.
Authors
- Rui Chen (ORCID: https://orcid.org/0000-0002-4787-2450)
- Fan Wang (ORCID: https://orcid.org/0000-0001-9461-7682)
- Hui Tian (ORCID: https://orcid.org/0000-0002-7982-0276)
- Xuzhao Yang
- Jinping Ni (ORCID: https://orcid.org/0000-0002-2685-7200)
Institutions
- Xi'an Technological University (CN)
Publication Details
- Journal
- Sensors
- Published
- 2025-04-27
- DOI
- https://doi.org/10.3390/s25092758
- Primary Topic
- Advanced Optical Sensing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00