一种基于高速数字FFT的超宽带实时频谱监测方法

By constructing a legitimate emission template set and using intelligent sensor sampling, combined with Fast Fourier Transform and wolf pack algorithm optimization, effective identification of hidden illegal emissions was achieved. This solves the problem of distinguishing between legitimate strong emission sources and illegal signals in existing technologies, and improves the accuracy and stability of spectrum monitoring.

CN122204623BActive Publication Date: 2026-07-17SHANGHAI XUNXI ELECTRONIC TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SHANGHAI XUNXI ELECTRONIC TECH CO LTD
Filing Date
2026-05-18
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing radio spectrum monitoring systems struggle to effectively identify illegal signals hidden within the spectrum structure of legitimate strong transmitters, especially when illegal transmitters deliberately approach the sidebands or pilots of legitimate strong transmitters. Conventional threshold detection and smoothing processes are insufficient to distinguish them from legitimate strong transmitters.

Method used

By constructing a set of legitimate transmission templates, using intelligent sensor sampling and fast Fourier transform to generate spectrum frames, performing frequency alignment, phase alignment and energy mapping, and after self-hiding processing, combining the wolf pack algorithm to optimize the templates, performing short-time cyclic feature tracking and cross-frame microstructure consistency determination, the hidden illegal transmissions are confirmed.

Benefits of technology

It improves the ability to identify illegal emissions hidden near legitimate high-power emission sources, reduces the false alarm rate, improves the accuracy of anomaly confirmation and the reliability of monitoring results, and forms a complete closed loop from raw sampling to monitoring result output.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明提供了一种基于高速数字FFT的超宽带实时频谱监测方法，包括：通过智能传感器接收目标监测频段内的射频信号，生成实时宽带采样帧，并对实时宽带采样帧执行快速傅里叶变换和有效性校验，得到待模板分析频谱序列；基于待模板分析频谱序列和合法信号标识库识别合法强发射源候选，提取导频位置特征、边带衰减特征、相位延续特征和包络变化特征，并利用狼群算法生成合法发射模板集；基于合法发射模板集生成合法预测频谱，对当前频谱帧执行自消隐处理并提取残差频谱序列；基于残差频谱序列执行短时循环特征追踪、导频外异常节律搜索和跨帧微结构一致性判定，得到候选隐藏发射集合。
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Citation Information

Patent Citations

  • Artificial neural network spectrum sensing method based on wolf pack optimization

    CN104092503A

  • Rapid recognition method for highly masking signals

    CN104539375A