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how to avoid negative frequencies that can be obtained from instantaneous frequency estimation using Hilbert transform?

Here is what I am doing:

  1. compute analytic signal, X = hilbert(x);
  2. from analytic signal, unwrap the instantaneous phase
  3. calculate instantaneous frequency from derivation (np.diff) of instantaneous phase

The problem I have is that the instantaneous frequency can contains negative frequencies (e.g. chirp signal).

This issue is also well descriped her:

Negative instantaneous frequency with hilbert transform using scipy hilbert

Hilbert Huang Transform: Negative value in instantaneous frequency

The best solution seems to be descriped here:

Overcoming the negative frequencies - Instantaneous frequency and amplitude estimation using Osculating Circle method

and here:

Instantaneous frequency estimation using Osculating Circle Method

An other matlab code snipped is posted here, but it has no results:

InstantFrequencyOCM​ethod

The question is, how to calculate the velocity vector of the particle and the Osculating Circle method from the analytic signal (in matlab or python)?

Thanks, Tobias

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1 Answer 1

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Don’t unwrap phase as bounded, but unwrap it as always increasing (or delta(ph)>=0).

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  • $\begingroup$ I am using numpy.unwrap and matlab and GNU Octave unwrap. Should I implement a different unwrap? $\endgroup$
    – togo_la
    Aug 24 at 18:20
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    $\begingroup$ The instantaneous frequency is the difference in phase of the current sample to the previous sample of the analytic signal. I don't think it's a good idea treat some small negative quantity $-|\Delta \phi|$ as a value close to $2\pi$. $\endgroup$ Sep 24 at 5:18

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