In order to perform star-identification with lower processing requirements, multi-dimensional techniques are implemented in this research as a database search as well as to create star pattern parameters. New star pattern parameters are presented which produce a well-distributed database, required by the database search algorithm to achieve the fastest performance. To mitigate problems introduced by the star pattern selection, incorrect entries are added to the database, which reduces the number of iterations of the run-time algorithm. The associated algorithms, star pattern parameters, and database preparation are collectively referred to as Multi-dimensional Star-Identification (Star-ND). The star pattern parameters developed may also be extended to star patterns with an arbitrarily large number of stars, while retaining the well-distributed property. The algorithm is contrasted with the current state-of-the-art star-ID algorithm, Pyramid. The database is found to grow linearly with the size of the star catalog, while Pyramid's database grows quadratically. The running time of Star-ND is found to be on average a factor of 25 times faster than the time for Pyramid.

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As the use of small satellites for advanced space missions continues to grow, the importance of low mass and cost three-axis attitude stabilization systems increases as well, with these systems requiring high accuracy attitude knowledge. Star trackers provide the most accurate attitude knowledge of any type of attitude sensor, but the high cost, size, and weight of commercial star trackers can be prohibitive to small satellite missions. Many simple star trackers have been developed using commercial off-the-shelf camera sensors and processing hardware, but the challenge remains in testing and characterizing these devices. A common solution is night sky tests, in which the star tracker is held up to the night sky to image the star field and perform attitude determination. Commercial star trackers, on the other hand, are regularly tested with manufacturer provided star field images that attach directly to the sensor. These methods, however, severely limit the sky conditions that can be used in testing. Night sky tests depend on weather and can only image regions of the sky the user has access to, while lab-based testing uses the few provided still images. This thesis presents a hardware-in-the-loop star tracker test bed developed for comprehensive ground-based testing of both in-house and commercial star trackers. The system consists of a small screen to display a star field, a simple in-house camera star tracker, and a microprocessor. This test bed allows any star field image to be simulated. The system is set up for use on a stationary tabletop, but its small size lends itself for use with a spacecraft dynamics platform, which can facilitate testing of control algorithms using real star tracker output.