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To be noted that I'm very new to this topic, I would like to understand the fundamentals of how to get Super Resolution in Frequency Domain estimation using the Compressed Sensing Model.

I am also looking for some references and Python/Matlab code that can help me.

Thanks a lot in advantage and happy new year, Luca

Royi
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Luca R
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1 Answers1

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You can employ Compressed Sensing / Sparse Representation for Super Resolution in Frequency Domain.

One way to do so is solving the problem:

$$ \arg \min_{\boldsymbol{x}} \frac{1}{2} {\left\| F \boldsymbol{x} - \boldsymbol{y} \right\|}_{2}^{2} + \lambda {\left\| \boldsymbol{x} \right\|}_{1} $$

Where the $ {L}_{1} $ norm is sparsity inducing regularization and $ F $ is the inverse DFT matrix.

Solving this, quite simple, optimization problem will yield Super Resolution of the DFT.
Super Resolution means, in that context, being able to resolve frequencies which are closer than what the observation time suggests:

enter image description here

In the above you can see the DFT of a sum of 2 sines with the given frequencies. The Gaussian model is using $ {L}_{2} $ for regularization (Which is basically damped zero padding).

You may see that the $ {L}_{1} $ could resolve the 2 sines even when they are only 0.5 [Hz] apart with an observation windows of 1 [Sec].

This is pretty nice...

Royi
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  • very interesting, could you link some refs? for code in particular – I.M. Jan 20 '21 at 02:44
  • @I.M., Thank you. Feel free to +1 if you found it interesting. There are actually much better methods as well. – Royi Jan 20 '21 at 10:51
  • sure, already +1, could you add code? – I.M. Jan 20 '21 at 15:49
  • @Royi, thanks for the good overview. I was interested in some more technical details, in particular on 1) how to treat complex values, and 2) the relationship between dictionary size and resolution in the spare domain (https://dsp.stackexchange.com/questions/72346/compressed-sensing-in-doa-processing) – Luca R Jan 22 '21 at 11:50
  • any considerations (observations) about my last comment? – Luca R Feb 01 '21 at 11:00
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    What issues do you see with Complex Numbers in the formulation above? By design $ F $ is a complex matrix. In the above the dictionary is fixed, not learned. It sets the grid hence the maximum potential resolution. – Royi Feb 01 '21 at 16:06
  • thanks Royi, I have accepted your answer, sorry for the delay : ) – Luca R Mar 18 '21 at 10:22