I have some data from a radar to process in order to find the moments and in turn the wind speeds. I have no prior knowledge in signal processing so it's giving me a hard time to estimate the noise level from this spectrum.

A sample power spectra for a range bin (height level) is depicted in the following image:
enter image description here

I have already done windowing (another question might be needed whether I did it correctly or not) using a hamming window (by the scipy.signal.hamming function) and FFT is applied (using scipy.fft.fft function). Now I want to estimate the noise level using the Hildebrand & Sekhon method, and this is where I have got stuck. Understanding it without some backgroud in signal processesing has proven to be quite difficult for me to implement the noise level estimation.

Could anybody explain how can I estimate the noise level in this spectrum using the Hildebrand & Sekhon method.

There's 1024 NFFT points in the spectrum.

  • $\begingroup$ If you do not get an answer here i suggest you try the PyART or wradlib gitter channel. There maybe radar experts there that can help you $\endgroup$
    – gansub
    Jul 22 '20 at 8:22

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