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Since the attitude determination accuracy is around 0.01° (1.75 × 10−4 rad) or worse (Nakamura et al. 2011), the positions of cloud patterns in L2b images fluctuate by more than a pixel due to errors in the attitude of the spacecraft (Ogohara et al. 2012).
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The accumulated errors in these attitude values are corrected using the constraint.
In addition, the uncertainty model errors always exist in the attitude dynamic system, which also put forward the higher performance requirements for the classical KF in attitude estimation problem.
We describe the method used to reduce the errors in spacecraft attitude and correct the geometry information, an improved limb-fitting technique originally described by Ogohara et al. (2012), in "Reliability of pointing correction by limb fitting" section.
In this paper, an approach named regularized robust filter algorithm is proposed to control the relative installation error of star tracker in the attitude measurement data.
In this section an attempt is made to remedy the situation by applying a slightly more generalized treatment to attitude errors in the CI algorithm.
Fig. 10 Trajectory of the end-effector Fig. 11 Angle variation of each joint Fig. 12 Change in the attitude and position of the end-effector Fig. 13 Error of the attitude and position of the end-effector Fig. 14 Change in the attitude and position of the end-effector Fig. 15 Control force of each joint.
In this paper, a robust filter for an in-flight alignment (IFA) is presented to effectively eliminate system errors in the case where a strapdown inertial navigation system (SDINS) has large initial attitude errors.
It's all in the attitude.
Although errors in the alignment of instruments can be reduced by stellar observations, errors in the spacecraft attitude still remain.
US officials identified errors in the reporting.
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