TY - CHAP
T1 - An image registration approach for accurate satellite attitude estimation
AU - Carozza, Ludovico
AU - Bevilacqua, Alessandro
AU - Gherardi, Alessandro
PY - 2009
Y1 - 2009
N2 - Satellites are controlled by an autonomous guidance system that corrects in real time their attitude according to information coming from ensemble of sensors and star trackers. The latter estimate the attitude by continuously comparing acquired image of the sky with a star atlas stored on board. Beside being expensive, star trackers undergo the problem of Sun and Moon blinding, thus requiring to work jointly with other sensors. The novel vision based system we are investigating is stand alone and based on an earth image registration approach, where the attitude is computed by recovering the geometric relation between couple of subsequent frames. This results in a very effective stand alone attitude estimation system. Also, the experiments carried out on images sampled by a satellite image database prove the high accuracy of the image registration approach for attitude estimation, consistent with application requirements.
AB - Satellites are controlled by an autonomous guidance system that corrects in real time their attitude according to information coming from ensemble of sensors and star trackers. The latter estimate the attitude by continuously comparing acquired image of the sky with a star atlas stored on board. Beside being expensive, star trackers undergo the problem of Sun and Moon blinding, thus requiring to work jointly with other sensors. The novel vision based system we are investigating is stand alone and based on an earth image registration approach, where the attitude is computed by recovering the geometric relation between couple of subsequent frames. This results in a very effective stand alone attitude estimation system. Also, the experiments carried out on images sampled by a satellite image database prove the high accuracy of the image registration approach for attitude estimation, consistent with application requirements.
U2 - 10.1007/978-3-642-10520-3_79
DO - 10.1007/978-3-642-10520-3_79
M3 - Chapter (peer-reviewed)
SN - 978-3-642-10519-7
VL - 5876
T3 - Lecture Notes in Computer Science
SP - 827
EP - 836
BT - Advances in Visual Computing
PB - Springer
T2 - 5th International Symposium on Visual Computing
Y2 - 30 November 2009 through 2 December 2009
ER -