One Thing Leads To Another

I think my plan to do a subspace ID on the actual disturbances as measured by the WFS is a good one, but it turned out that the code we have to do it requires the measurements to be on a square grid. Stupidly, I've been using a rectangular 19x22 measurement area on the WFS, with the DM area (found by adding all the influence functions) shifted to the right by around 5 columns. Putting disturbances from a state space model on this odd configuration required scaling the image, shifting it in an attempt to align it with the DM area, an only then performing a least-squares fit with the poke matrix. Naturally the results were shit, as shown in the video in 6.18.10.

My slope calculation code is ludicrously cumbersome, so it took a day to properly rewrite it to use a 19x19 grid (actually a down-sampled 38x38 grid) and make sure it was bug-free. Realigning the beam and removing tilt so that the area for both DMs was centered took another. My advisor commented that he doesn't know how I keep everything straight in my head with so much shit going on. I assured him I have no idea what I'm doing.

Anyway, its good to periodically tinker with the experiment and realign everything anyway to keep my monkey skills sharp. Today I put some state-space generated disturbances on the DM, which now only requires rescaling the state-space output to a slightly larger grid. The resulting phases look much better. Here's a comparison between (L to R) the state-space output (1 phase screen model on a 17x17 grid), the DM phase predicted using the poke matrix (on a 19x19 grid), and the actual phase measured by the WFS (with the bias removed of course).



If you squint you can actually see the similarity in the phases as it flows across the aperture. Either way it much cleaner than the random flatulence I was getting before.

Tomorrow I'll look at how this affects the performance of the adaptive loop. Now that the grid is square I can also go ahead with my original plan and compute an optimal FIR filter.