  We have developed a low-cost off-the-shelf component star sensor (StarSense)
for use in minisatellites and CubeSats to determine the attitude of a satellite
in orbit. StarSense is an imaging camera with a limiting magnitude of 6.5,
which extracts information from star patterns it records in the images. The
star sensor implements a centroiding algorithm to find centroids of the stars
in the image, a Geometric Voting algorithm for star pattern identification, and
a QUEST algorithm for attitude quaternion calculation. Here, we describe the
software package to evaluate the performance of these algorithms as a star
sensor single operating system. We simulate the ideal case where sky background
and instrument errors are omitted, and a more realistic case where noise and
camera parameters are added to the simulated images. We evaluate such
performance parameters of the algorithms as attitude accuracy, calculation
time, required memory, star catalog size, sky coverage, etc., and estimate the
errors introduced by each algorithm. This software package is written for use
in MATLAB. The testing is parametrized for different hardware parameters, such
as the focal length of the imaging setup, the field of view (FOV) of the
camera, angle measurement accuracy, distortion effects, etc., and therefore,
can be applied to evaluate the performance of such algorithms in any star
sensor. For its hardware implementation on our StarSense, we are currently
porting the codes in form of functions written in C. This is done keeping in
view its easy implementation on any star sensor electronics hardware.
