| 李浩,王煌辉,曹佳伟,卫洋斌,李旭阳.基于Zoom-FFT算法的实时频谱分析方法[J].电子测量与仪器学报,2025,39(7):32-44 |
| 基于Zoom-FFT算法的实时频谱分析方法 |
| Real-time spectrum analysis method based on Zoom-FFT algorithm |
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| DOI： |
| 中文关键词: 实时频谱 Zoom-FFT 重叠帧 加窗 频谱计算 |
| 英文关键词:real-time spectrum Zoom-FFT overlapping frame add windows spectrum calculation |
| 基金项目:国家自然科学基金（62303091）、中央高校基本科研业务费专项基金（ZYGX2022J015）、中国博士后科学基金（2021M700707）、四川省自然科学基金（2022NSFSC0905）项目资助 |
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| Author | Institution |
| Li Hao | School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China |
| Wang Huanghui | School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China |
| Cao Jiawei | School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China |
| Wei Yangbin | School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China |
| Li Xuyang | School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China |
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| 中文摘要: |
| 随着现代通信与信号处理系统对实时性和高分辨率需求的不断提升，传统快速傅里叶变换(FFT)在频谱分析中存在频率分辨率与带宽之间的矛盾逐渐突显，难以兼顾实时处理与高精度分析的需求。针对这一问题，提出了一种基于Zoom-FFT算法的实时频谱分析方法，旨在通过局部频谱细化技术，在降低计算复杂度的同时实现高分辨率频谱分析，并满足实时性要求。该方法通过数字下变频技术将目标频段信号搬移至基带，采用多级抽取滤波对信号进行降采样和低通滤波，在压缩数据量的同时保留目标频段特征通过FFT算法对降采样的信号进行局部高分辨率计算，提升了对微弱信号的检测能力，同时引入重叠帧技术减少频谱泄漏与提升频谱更新速率。最后在现场可编程门阵列（FPGA）硬件上完成部署和验证。实验结果表明，在250 MHz采样率下，该方法对50 kHz带宽信号的频率分辨率达到了1 kHz，通过FPGA并行化架构优化，增强了数据处理效率。该方法通过流程创新与硬件加速协同，为通信信号监测与雷达脉冲分析等场景提供了高实时性、高精度的频谱分析方案。 |
| 英文摘要: |
| With the increasing demand for real-time processing and high resolution in modern communication and signal processing systems, the inherent trade-off between frequency resolution and bandwidth in traditional FFT-based spectral analysis has become increasingly evident, making it challenging to simultaneously achieve rapid processing and high-precision analysis. To address this issue, this paper proposes a real-time spectral analysis method based on the Zoom-FFT algorithm. The proposed approach leverages a localized spectral refinement technique to perform high-resolution spectral analysis while reducing computational complexity and satisfying real-time requirements. In this method, the target frequency band is first down-converted to baseband using digital down-conversion. Multistage decimation filtering, incorporating both low-pass filtering and down-sampling, compresses the data while preserving essential spectral features. Subsequently, a localized high-resolution FFT is applied to the decimated signal, which enhances the detection capability for weak signals. An overlapping frame technique is also introduced to mitigate spectral leakage and improve the spectrum update rate. The method is ultimately implemented and validated on FPGA hardware. Experimental results indicate that, at a sampling rate of 250 MHz, the proposed method achieves a frequency resolution of 1 kHz for a signal with a 50 kHz bandwidth, while the FPGA’s parallel architecture further improves data processing efficiency. This integrated approach of innovative signal processing and hardware acceleration provides an effective solution for high-real-time and high-precision spectral analysis in applications such as communication signal monitoring and radar pulse analysis. |
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