Me And My Astro

I have been an active and avid photographer since middle school, and took a major in photojournalism at Indiana University. I’ve been interested in the night sky the whole time, starting when I had an amateur astrophotographer for a next-door neighbor and bought a copy of Make Your Own Telescope (though all I have to show for that effort is a slightly frosty patch on a 10-inch mirror blank).

I started doing night landscapes in 2010 or so, and have slowly edged deeper into space (and farther back in time) as I acquired interest, skills, and equipment.

Today, I still do night landscape work with equipment no more sophisticated than a DSLR and a tripod; heck, one of my recent favorites was hand-held with my cell. But I especially love deep sky imaging, faint fuzzies seen by light that left home thousands or millions of years ago.

The 8” Richey-Chrétien reflector at right is my go-to “galaxy cannon” for small targets (1° angular size or less). It mounts a thermoelectrically cooled monochrome astro camera and a wheel with red, green, and blue filters for stars and galaxies, as well as filters that pass just a single common element’s emission wavelength for emission nebulae. The white 3D-printed box on top contains the brains, with a Raspberry Pi and Arduino that figure out what’s where in the sky and run the cameras and telescope.

If I want a wider field of view, I use a much smaller refractor scope, or can put a DSLR and lens on the mount.

The Pi, running StellarMate OS, points the scope to the target I select, sequences the frames, selects the desired filter from the wheel, and operates the autofocuser. It also runs a secondary guide camera that images stars every few seconds, analyzing their apparent movement to provide minute corrections to the mount. It has to track to sub-arcsecond precision (i.e., the apparent size of a dime held up three miles away) during the exposures or the details are blurred and the stars look fuzzy. Sometimes I’m doing 10-minute exposures, so we are talking a frankly amazing degree of accuracy here!

Once I’ve got the frames*, computer magic begins. Shooting a bunch of sub-exposures allows all sorts of tasty math to winnow out signal from noise and ameliorate light pollution, satellite trails, moonlight, and just the inescapable fact that I’m collecting just a handful of photons per second from these very dim objects.

The basic idea is that each pixel of each frame will have a noise component, whether just statistical variation in the numbers of photons that have arrived or something inherent in the optics or electronics. By averaging (“stacking”) multiple images and using calibration frames to filter out fixed and known noise sources, stacking homes in on the “true” value of each pixel.

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* Which assumes, of course, that all this hardware and software functions correctly. Never will forget the Texan visual astronomer who told me “In my experience, an imager is a guy standin’ in the dark swearin’ at somethin’ that ain’t workin’.” He’s not wrong.