Mathematics
Scientific paper
May 1995
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995fmet.symp..167w&link_type=abstract
In its Flight Mechanics/Estimation Theory Symposium 1995 p 167-172 (SEE N95-27763 09-13)
Mathematics
Algorithms, Attitude (Inclination), Attitude Indicators, Ccd Star Tracker, Charge Coupled Devices, Explorer Satellites, Real Time Operation, Robustness (Mathematics), Solar Sensors, Astronomical Catalogs, Attitude Control, Ground Based Control, Prototypes, Slits, Stellar Models
Scientific paper
The Advanced Composition Explorer (ACE) spacecraft is designed to fly in a spin-stabilized attitude. The spacecraft will carry two attitude sensors - a digital fine Sun sensor and a charge coupled device (CCD) star tracker - to allow ground-based determination of the spacecraft attitude and spin rate. Part of the processing that must be performed on the CCD star tracker data is the star identification. Star data received from the spacecraft must be matched with star information in the SKYMAP catalog to determine exactly which stars the sensor is tracking. This information, along with the Sun vector measured by the Sun sensor, is used to determine the spacecraft attitude. Several existing star identification (star ID) systems were examined to determine whether they could be modified for use on the ACE mission. Star ID systems which exist for three-axis stabilized spacecraft tend to be complex in nature and many require fairly good knowledge of the spacecraft attitude, making their use for ACE excessive. Star ID systems used for spinners carrying traditional slit star sensors would have to be modified to model the CCD star tracker. The ACE star ID algorithm must also be robust, in that it will be able to correctly identify stars even though the attitude is not known to a high degree of accuracy, and must be very efficient to allow real-time star identification. The paper presents the star ID algorithm that was developed for ACE. Results from prototype testing are also presented to demonstrate the efficiency, accuracy, and robustness of the algorithm.
Rohrbaugh Dave
Woodard Mark
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