I have searched Stackexchange forums for ideas, but could not find anything useful for me. I am registering real-time stability of the He-Ne laser interferometer by analyzing interference fringe movement on CCD linear sensor. I am getting data samples every 15-20 ms, data looks like this: enter image description here

Now if interference conditions changes, fringes move - phase of this modulated signal changes:

enter image description here

So my first quite successful method was to take one peak, fit it with Gaussian, register it's center position over time and calculate difference from the first sample, then normalize it to distance between two peaks and get phase change over time.

But now I want to calculate this more "elegantly" and to use all fringes, not only one peak. So I thought maybe I could use Fourier transform. When I use FFT, I get spatial-frequency of this modulation. The problem is, I don't how to proceed further and extract phase information, so here comes my question. How algorithm with Fourier transform should look like, or maybe there is other better methods (maybe some kind of correlation)?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.