Signal/Data Processing Question

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Methods for separating signal from noise in data sets include band-separation techniques, particularly when the signal is lower frequency than the noise. High amplitude spikes may represent either reliable signal components or synchronous noise, necessitating further clarification on the data type, such as RF signal strength or radar pulses. The discussion raises questions about the noise floor, suggesting that variations may stem from different termination resistors or preamp configurations. Additionally, the availability of the raw signal before log detection is questioned, emphasizing the need for clear definitions of the ideal signal. Understanding these factors is crucial for effective signal processing.
crispyrice2008
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Hi,

I'm curious if there is a method to separate the signal from the noise in this kind of data set, other than manually do it by indexing.
the top plot is the data, the bottom plot is the zoom in of the data.
the time length for signal & data are relatively constant throughout the data, it always follow the order: noise, data, noise, data...


2eobpra.png
 
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Looks like the signal is lower frequency than the noise. Can you band-separate the signal from the noise?
 
Welcome to PF>

What are the regular high amplitude spikes? a reliable part of the the signal or synchronous noise?
What is the data? Is it RF signal strength in dB from a log detector? Maybe radar pulses?
Is it output from a two channel switching detector, so an application for a boxcar integrator?

Why is the noise floor with signal lower than without signal?
Is it a 50 ohm termination resistor at room temperature compared to a FET low noise signal preamp?

Is the raw signal, IF, available before log detection?

We cannot find something if we do not know what you are looking for.
I think it is necessary for you to define or identify what an ideal signal without noise would be.
 
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