Computer Science – Performance
Scientific paper
Aug 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005spie.5916..292n&link_type=abstract
Mathematical Methods in Pattern and Image Analysis. Edited by Astola, Jaakko T.; Tabus, Ioan; Barrera, Junior. Proceedings of t
Computer Science
Performance
Scientific paper
The MicroMak device is a new, high-precision, very compact star sensor weighing less than 100 grams, with three independent 4-degree square fields of view. The collection telescope is a Maksutov design that incorporates three telescopes into a single sensor head. The sensor is designed for star identification and spacecraft attitude determination with a device that offers unprecedented low cost, volume and mass. While star trackers have achieved sub-arcsecond accuracy by utilizing sophisticated algorithms and complex hardware, the MicroMak sensor must rely on fairly efficient algorithms that utilize data from only the image sensor. This paper will discuss the attitude determination algorithm as well as a complete end-to-end simulation of the system that was used to optimize the design and predict performance. This simulation accepts various star and sensor parameters as inputs, and generates error estimates of attitude of the sensor. The inputs include color temperatures and magnitudes of stars, focal length, receiver aperture, reflectivity curves of mirrors, modulation transfer function of the telescope system, vignetting effects, jittter characteristics, spacecraft spin rate and spin axis, detector pixel size, read noise, dark noise, sensor update rate, quantum efficiency as a function of wavelength, and detector fill factor. A complete forward model of the optical train has been built, and used with a maximum likelihood estimator to generate estimates of sensor attitude. A Monte Carlo algorithm was used to generate error distributions on the attitude error given the noise and distortions injected into the measurement.
Hays Paul B.
Nardell Carl A.
Wertz James
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