Broadband Signal Blind Detection Performance Optimization based on DiffBIR Model

CAO Wenqiang; CHEN Yarong; ZHU Rui; ZHANG Hong; HAN Ding

doi:10.13756/j.gtxyj.2026.240104

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Broadband Signal Blind Detection Performance Optimization based on DiffBIR Model

更新时间：2026-03-03

- Broadband Signal Blind Detection Performance Optimization based on DiffBIR Model
- Study on Optical Communications Issue 1, (2026)
- 作者机构：
  
  1.西京学院　电子信息学院，西安　 710123
  2.联勤保障部队第五工程代建管理办公室，武汉　 430000
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2026.240104
  CLC： TN929
- Received：30 May 2024，
  
  Revised：2024-07-22，
  
  Published：10 February 2026
- 稿件说明：
移动端阅览
曹文强，陈雅蓉，朱锐，等. 基于DiffBIR模型宽带信号盲检测性能优化[J]. 光通信研究，2026(1): 240104.

Cao W Q, Chen Y R, Zhu R, et al. Broadband Signal Blind Detection Performance Optimization based on DiffBIR Model[J]. Study on Optical Communications, 2026(1): 240104.
曹文强，陈雅蓉，朱锐，等. 基于DiffBIR模型宽带信号盲检测性能优化[J]. 光通信研究，2026(1): 240104. DOI： 10.13756/j.gtxyj.2026.240104.

Cao W Q, Chen Y R, Zhu R, et al. Broadband Signal Blind Detection Performance Optimization based on DiffBIR Model[J]. Study on Optical Communications, 2026(1): 240104. DOI： 10.13756/j.gtxyj.2026.240104.

摘要

目的

针对低信噪比（SNR）环境下非合作通信宽带信号盲检测效果不佳的问题，文章旨在通过创新预处理策略提升信号检测性能，确保复杂电磁环境中通信的可靠性与稳定性。

方法

文章提出了一种新颖的信号预处理与检测框架，其核心在于运用生成扩散先验的图像盲恢复（DiffBIR）模型。DiffBIR模型是一种集成了去噪、去模糊及超分辨率技术的先进图像处理方法，经文献检索确认，该模型在宽带接收信号时频图优化中的应用尚未见公开报道，具有创新性。具体实施中，先借助Diff-BIR模型处理增强信号时频特征，随后利用Matlab平台集成的连通组件分析算法进行精细化信号检测，以期在低SNR场景下实现更精准的信号识别。

结果

实验结果显示，该方案在-15~-25 dB的低SNR测试条件下，相较于传统未优化方法，检测精确率提升了133%，召回率增加了32%，且综合评价指标F1分数也实现了139%的增长。这些数据明确反映出，经过DiffBIR模型预处理后的信号在保持高召回的同时，显著提高了检测的精确性。

结论

文章成功构建了一套基于DiffBIR模型的宽带信号盲检测技术体系，有效克服了低SNR环境下信号检测的挑战。该技术不仅极大增强了信号的可检测性和识别精度，还在实践中展示了其应用于复杂电磁环境的潜力，为军事及民用通信系统的信号处理提供了新的理论基础和技术途径，具有重要的理论价值和实践意义。

Abstract

Objective

Aiming at the problem of poor blind detection effect of non-cooperative broadband signal in low Signal-to-Noise Ratio (SNR) environment

this study aims to improve signal detection performance through innovative preprocessing strategies to ensure communication reliability and stability in complex electromagnetic environment.

Methods

A novel signal preprocessing and detection framework is proposed

the core of which is the Blind Image Restoration with Generative Diffusion Prior (DiffBIR) model. DiffBIR model is an advanced image processing method which integrates de-noising

de-blurring and super-resolution techniques.A literature review confirms that the application of this model in the optimization of time-frequency graphs for wideband received signals has not been publicly reported

making it innovative. In the specific implementation

DiffBIR processing is first used to enhance the signal time-frequency characteristics. Then the connected component analysis algorithm integrated with Matlab platform is used to fine signal detection

in order to achieve more accurate signal recognition in the low SNR scenario.

Results

Experimental verification showed that under the low SNR test conditions of-15~-25 dB

compared with the traditional non-optimized method

the detection accuracy rate was increased by 133%

the recall rate was increased by 32%

and the F1 score of the comprehensive evaluation index was also increased by 139%. These data clearly reflect that DiffBIR pretreated signals can significantly improve detection accuracy while maintaining high recall.

Conclusion

In this study

a set of broadband signal blind detection technology system based on DiffBIR model is successfully constructed

which effectively overcomes the challenge of signal detection in low SNR environment. This technology not only greatly enhances the detectability and identification accuracy of signals

but also shows its potential application in complex electromagnetic environment in practice. It provides a new theoretical basis and technical approach for signal processing of military and civil communication systems

and has important theoretical value and practical significance.

关键词

Keywords

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