I always preface these posts with, “I don’t talk about work, but…” In this case, what I wrote is for public consumption and is up on the web, so I figure it’s okay. My company works on ways to measure where one spacecraft is relative to another. We’re applying some of that technology to the Hubble Space Telescope. The Hubble’s dying, and needs repairs, but NASA’s leery about sending astronauts to it, since if something happens to the Shuttle, they’d be unable to reach the International Space Station. So the next mission to Hubble is likely to be the last one unless they can come up with a way for robots to do the repair job.

That’s where we come in. For a spacecraft to reach Hubble without a pilot at the stick, the onboard computer has to know where Hubble is. We’ve got a way to do that. Behold: using video to measure the Hubble’s position and orientation in orbit.

[tags]space, hubble space telescope, the things you can do with cameras these days[/tags]

Hey that’s cool stuff Stephen. So, I’m a bit curious. In RF I know what a Fourier Transform of a signal means. But, I’m not really sure how you take the F.T. of an image. Or what exactly that gives you. Does that involve looking at the luminance of the image? The color map? Some combination of it?

In our case, we’re doing a two-dimensional fourier transform of the intensity of the image (like 0 to 255 greyscale). You perform the Fourier transform over the x and y axes and what you get out is a map of the frequency response along x and along y.

Correlation, in the Fourier domain, involves multiplying two Fourier-transformed signals together. In this case we Fourier transform the image and compare it to various filters — bits of reference images we’ve already Fourier transformed. If the bits of reference image appear somewhere in the first image, then we’ll get a peak in the Fourier plane that corresponds to where the reference image is.

Yea that makes since. Neat stuff, I never actually knew *what* you did nice to get an idea = )