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Stationary Wavelet Packet Programmable Filters for Real Time Signal Detection and Denoising

机译:用于实时信号检测和去噪的固定小波包可编程滤波器

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In this work we present a new methodology for Radar or Sonar pulses detection and filtering in presence of strong noise and jamming signals. The detection and denoising can be obtained through an hard thresholding or a pattern matching procedure performed on the coefficients resulting from a Stationary Wavelet Packet Transform analysis on the noisy signal. When the knowledge of the ideal received signal spectrum is given, we can select the optimus wavelet packet tree, and then filter the frequencies out of the sig-nal band. Moreover, we give useful guidelines to design hardware implementation of the proposed algorithm steps, to perform a real time pulse detection and denoising. The architecture is easily reconfigurable, so we can eventually redirect the analysis to different wavelet packet domains.
机译:在这项工作中,我们提出了一种在存在强噪声和干扰信号的情况下用于雷达或声纳脉冲检测和滤波的新方法。可以通过对噪声信号进行固定小波包变换分析得出的系数,通过硬阈值或模式匹配过程来获得检测和降噪效果。在给出了理想的接收信号频谱的知识后,我们可以选择最优小波包树,然后对信号频带之外的频率进行滤波。此外,我们提供了有用的指南来设计所提出算法步骤的硬件实现,以执行实时脉冲检测和去噪。该架构易于重新配置,因此我们最终可以将分析重定向到不同的小波包域。

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