从信号中去除不需要的方波噪声

信息处理 信号分析 噪音 海浪
2022-02-14 16:40:41

在此处输入图像描述

我在此消息的末尾给出了一个信号 s。我需要从中删除方波形状。所需信号实际上非常小，并且已被强烈的方形噪声污染。

所需信号只是类似于 ECG 或 EEG 的几个峰值，但我们有一个非常大的方形噪声，会随机影响一些扫描结果。

中心频率 = 10MHz，采样频率 = 125MHz

（请注意，这些是与红色信号和发送超声波脉冲的机器人换能器相关的频率。这些不是蓝色信号的频率，也不是方波的频率。）

s = 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3个回答

添加完整信息后，您的问题现在非常有趣。（我现在赞成问题）

我对使用数字信号处理技术处理此类信号的尝试持怀疑态度。在进行任何数字信号处理之前，专注于减少记录信号中的“方波噪声”。首先检查这种噪声的性质——它可能是声音（即机器人的声音，由扫描仪的接收器记录），也可能是电的（例如机器人电源的噪声传播到扫描仪电源）供应或直接到接收器电路等） 。根据这项研究的结果，尝试减少扫描仪信号上的这种噪声。例如，如果是机器人发出的声音 - 尝试在接收器前面添加吸音器。您可以尝试从扫描仪外部录制声音，然后从扫描仪的信号中减去它。如果从机器人的电源电路中拾取 - 改善扫描仪电路的保护。在实验物理学中，有很多方法和技术可以解决这些问题，但往往更像是艺术。

祝你好运！

如果您知道方波信号的来源，或者可以单独锁定它，请在任何其他滤波之前将该方波的反相、幅度调整版本与您的噪声输入相加。您还可以对剩余信号使用同步检测原理来检测方波贡献，然后在检测到所需信号后将其以 DC 方式减去。我在这里有一个关于同步检测的 GoogleDocs 集合：

如果您在访问它时遇到问题，请告诉我。

我想起了一种叫做“unsharp-masking”的图像处理技术你的目标是增加图像的清晰度（高频）。它是通过模糊图像（增加低频）来实现的。然后从原始频率中减去模糊版本，因为原始频率 - 低频率 = 高频率。也许这可以在这里应用，因为您的噪声频率比您的信号低得多，而且您的信号似乎是 0 均值。

您对波形进行了一个小的滑动窗口平均值（这相当于模糊）。然后从原始数据中减去滑动窗口平均重建。只留下你想要的信息。

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