基于STFrFT-IG的管状结构内目标测速方法研究

    Research on Velocity Measurement Method of Targets Inside Tubular Structures Based on STFrFT-IG

    • 摘要: 针对微波干涉仪在管状结构内目标测速过程中,强干扰、强振动、强冲击等恶劣环境导致微波干涉回波信号信噪比低,测量精度严重下降等问题,提出了一种基于短时分数阶傅里叶变换与信息几何的管状结构内测速信号处理方法。该方法在对微波干涉仪采集的回波信号进行趋势项去除和小波降噪预处理后,重点利用短时分数阶傅里叶变换进行时频分析,通过抛物线插值与频率跟踪技术提取出管状结构内目标瞬时频率,根据多普勒原理计算管状结构内目标初始速度。进一步将STFrFT(Short-Time Fractional Fourier Transform,短时分数阶傅里叶变换)时频幅度谱映射为概率分布,以提取的雷达回波趋势项作为参考分布,基于KL(Kullback-Leibler)散度与Fisher信息度量构造速度校准方法,采用自然梯度下降算法对管状结构内目标初始速度曲线进行迭代校准,最终完成管状结构内目标的高精度速度测量。仿真实验和实测信号处理结果表明:相较于传统STFT(Short-Time Fourier Transform,短时傅里叶变换)与WVD(Wigner-Ville Distribution,维格纳-维尔分布)方法,所提方法在低信噪比条件下具有更优的时频分辨率与抗干扰能力。在-10 dB低信噪比仿真环境下,以未采用信息几何校准的STFrFT方法为对比基准,本算法平均绝对误差与标准误差较STFrFT分别降低26.7%与26.4%,且在实测数据处理中本算法的最大速度绝对误差为1.34m/s,对应的满量程相对误差为0.0904%,为复杂环境下管状结构内目标运动参数测试提供了方法参考。

       

      Abstract: To address the critical issues in target velocity measurement inside tubular structures using microwave interferometers—including low signal-to-noise ratio (SNR) of microwave interference echo signals and severe degradation of measurement accuracy induced by harsh working environments such as strong interference, intense vibration and heavy impact—this paper proposes a signal processing method for in-tubular-structure velocity measurement based on the short-time fractional Fourier transform (STFrFT) and information geometry (IG). First, the echo signals acquired by the microwave interferometer are preprocessed via trend term elimination and wavelet denoising. Subsequently, the STFrFT is adopted for time-frequency analysis. Instantaneous frequencies of targets inside the tubular cavity are extracted by means of parabolic interpolation and frequency tracking techniques, and the initial velocity of the in-cavity targets is calculated in accordance with the Doppler principle. Furthermore, the time-frequency amplitude spectrum obtained from STFrFT is mapped into a probability distribution, and the extracted trend term of radar echoes is taken as the reference distribution. An optimized algorithm framework is constructed based on the Kullback-Leibler (KL) divergence and Fisher information matrix. The natural gradient descent algorithm is utilized to iteratively calibrate the initial velocity curve of targets within the tubular structure, ultimately realizing high-precision velocity measurement of internal targets. Results of both simulation experiments and measured signal processing demonstrate that the proposed method achieves superior time-frequency resolution and anti-interference capability under low-SNR conditions compared with conventional short-time Fourier transform (STFT) and Wigner-Ville distribution (WVD) algorithms. In simulation environments with an SNR of −10 dB, the mean absolute error and standard deviation of the proposed algorithm are reduced by 26.7% and 26.4%, respectively, relative to the standalone STFrFT method. Moreover, the practical velocity measurement accuracy inside actual tubular structures exceeds 0.030%. This work provides a methodological reference for measuring motion parameters of targets inside tubular structures under complex harsh environments.

       

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