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利用匹配傅里叶变换和二维解卷积的时变线谱信号长时处理方法

Long-time signal processing algorithm for moving targets based on deconvolution two-step matched Fourier transform

  • 摘要: 水下运动目标辐射的线谱信号具有时变性, 导致长时信号处理性能下降。针对这一问题, 提出了利用匹配傅里叶变换和二维解卷积的时变线谱信号长时处理方法(dTMFT)。所提方法聚焦时变线谱信号的二阶多项式相位时变特征, 利用二步匹配傅里叶变换(TMFT)使得时变线谱信号能量在频率和频率变化率维度形成良好聚焦性。进一步, 利用Richardson-Lucy算法对TMFT输出进行解卷积处理, 有效抑制TMFT输出中的放射状高旁瓣并降低输出背景级。数值仿真和海上实测数据分析表明, 所提方法在保持优异的时变线谱信号长时处理能力的同时, 可有效削弱旁瓣带来的影响, 从而清晰地分辨目标并降低输出背景。

     

    Abstract: The time-varying line spectrum signals from underwater moving targets cause performance degradation in long-duration processing. A method based on matched Fourier transform (TMFT) and two-dimensional deconvolution, called dTMFT, is proposed to address this. The second-order polynomial phase characteristics of the signals are focused on, and a two-step TMFT is used to concentrate energy in frequency and frequency rate dimensions. The TMFT output is then deconvolved using the Richardson-Lucy (R-L) algorithm, effectively suppressing radial sidelobes and background levels. Simulations and real sea trial data processing confirms enhanced target resolution and reduced background levels while maintaining long-duration processing capability.

     

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