aztennenbaum edited this page Jan 15, 2018 · 1 revision


A fast, robust, open source startracker based on a new class of baysian startracker algorithms


  • Fast lost in space identification
  • Image to image matching
  • Collect and store size, shape and color information of unknown objects
  • Tracks unknown objects between images
  • Programable python frontend / reusable C++ backend (BEAST-2) with no external dependencies
  • Uses for calibration (check if your camera is good enough by uploading your star images to

Basic setup:

From a fresh xubuntu 16.04 linux install

Development computer setup:

sudo apt-get install git libvte-dev libtool ctags gdb meld nemiver libwebkit-dev vim geany geany-plugins python-astropy  g++-multilib

Note: The following also needed for actually building (ie. on flight computer)
sudo apt-get install python-scipy libopencv-dev python-opencv swig
cd /usr/share/astrometry

Download fits files corresponding to your camera fov size (see for details
sudo wget
sudo wget
sudo wget
sudo wget
sudo wget
sudo wget
sudo wget
sudo wget

git clone

cd openstartracker/tests
./ -crei xmas
To calibrate a new camera:
cd openstartracker/
mkdir yourcamera
mkdir yourcamera/samples
mkdir yourcamera/calibration_data

add 3-10 star images of different parts of the sky taken with your camera to yourcamera/samples

edit APERTURE and EXPOSURE_TIME in (you want to take images with the lowest exposure time that consistently solves)

run ./ -crei yourcamera to recalibrate and test

The ESA test should have a score of >70. If its worse than this, play around with exposure time (50ms is a good starting point)

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