Find Frequencies in Signal with Random Sample Rate

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Discussion Overview

The discussion revolves around the challenge of finding frequencies in a signal that has been sampled at random intervals. Participants explore various methods and considerations for analyzing such signals, particularly in the context of frequency estimation and the implications of sampling rates.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant inquires about the nature of the sampling, questioning whether the sample rate is unknown, the intervals are random, or if there are time tags for each sample.
  • Another participant emphasizes the necessity of having information about the timing of measurements to estimate frequency accurately.
  • A different viewpoint suggests that random sampling must exceed the Nyquist rate to avoid distortion, noting that longer sample intervals could introduce quantization noise.
  • One participant recommends using Least Squares Spectral Analysis (LSSA) instead of FFT for data sampled at random intervals, mentioning its efficiency for periodic signals but expressing uncertainty about its performance for non-periodic signals.
  • Another participant asks for clarification on the timing of the sampling, indicating that timing is crucial for frequency analysis.
  • The original poster mentions contacting the manufacturer of their measuring device to potentially adjust the sample rate, indicating an exploratory approach to resolving their issue.
  • The original poster later clarifies that the timing of their samples is periodic, with specific intervals between samples.

Areas of Agreement / Disagreement

Participants express varying levels of understanding and approaches to the problem, with no consensus reached on the best method for frequency analysis in the context of random sampling. Multiple competing views and suggestions remain present throughout the discussion.

Contextual Notes

There are limitations regarding the assumptions about the sampling intervals and the potential effects of sampling below the Nyquist rate, which have not been fully resolved in the discussion.

liquidFuzz
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Hi

How do I find the frequencies in a signal obtained by samplings with a random sample rate? Normally I use a fft analysis, but then I have a fixed sample rate.

Thanks!
 
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I don;t understand the questions
Do you mean that you don't know the sample rate?
Or that the signal was sampled at random intervals?
Or that it was sampled at random intervals but you know WHEN the measurement was done (i,e., each sample has a time tag)?

Regardless, you obviously need SOME form of information about the timing of the measurement to estimate the frequency.
 
If you use a random sampling method then it must always be faster than the Nyquist rate. If some samples are spaced longer than the Nyquist interval then there will be random errors on the recovered signal. This amounts to a source of noise which accompanies the signal, and amounts to quantisation noise. Any sampling below the Nyquist rate will produce gross distortion.
 
If you're talking about data sampled with random intervals (as opposed to constant intervals where you'd use the FFT), then instead of FFT, you want to use LSSA. There's an efficient implementation in Numerical Recipes in C (I don't have it on me or I would give you the chapter number).

Other implementations:
Scipy
Matlab

LSSA is recommended when you expect a periodic signal. I've looked in the literature before but never found answers about how it performs for spectral analysis of non-periodic signals (noise power spectra, for example).
 
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Time is of the essence. What do you know about the timing of your sampling?
 
Thanks for all the input! I'll check the numerical approach suggested.

So far I only really tried to attack the issue by contacting the manufacturer of the measuring device I'm tinkering with to see if I can change the sample rate.
 
Oh, i forgot mentioning. The timing is periodic atm. 0,335 and 0,408 between samples. The 0,335 is used 5 times for each 0,408 timing.
 
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