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to OpenStartracker
By 05/24/2018: Detailed derivation of openstartracker via probability theory Probability theoretic derivation of probability of match Camera misalignment correction In space camera misalignment correction procedure.
By 08/01/2018: Easy in space recalibration Add "just distractors" unit test Rewrite openstartracker algorithm as classes with fewer side effects Faster algorithm based on constellation probabilities rather than individual star probabilities
By 01/01/2019: Distinguish non-stars from stars via eigenvector medthods and frame to frame relative position (H0: motion due to centroiding noise; H1: motion due to not being a star) Proper data collection for non-stars Distortion correction Save and load databases
By 01/01/2019 (depending on various factors): Documentation on image mask, collision resolution, weighted triad (may change) Use Tetra for calibration
Future work: Setup continuous integration For initial guess, generalize constellations to allow a user selectable number of stars rather than just 2 GPU/multicpu parallelization Add brightness Neural net centroiding/ non-blind motion blur compensation Reconstruct large field of view using multiple images taken over time Multi camera startracking Earth tracker Horizon sensor Moon tracker Sun tracker Delay compensation