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Although errors in the alignment of instruments can be reduced by stellar observations, errors in the spacecraft attitude still remain.
One case of considerable interest is that the errors are autoregressive processes; Hu [10], Wu [11], and Fox and Taqqu [12] established its asymptotic normality with the usual p n -normalization in the case of long memory stationary Gaussian observations errors.
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It is shown that the observation errors obtained from the observer are uniformly ultimately bounded.
A sliding mode observer is derived such that the observation errors converge to zero asymptotically in fInite time.
An optimized observer based on acceleration feedback (Accelerometer-based observer) reduces observation error under tire nonlinear adhesion limit conditions.
The term "Gaussian distribution" refers to the German mathematician Carl Friedrich Gauss, who first developed a two-parameter exponential function in 1809 in connection with studies of astronomical observation errors.
Thin lines show observation errors.
Figure 8 Dynamics of the observation errors.
Both process (recruitment) and observation errors were considered.
We explicitly include systematic error sources in addition to uncorrelated random observation errors.
Current CEDO methods only consider observation errors and focus on problems with low-dimensional response variables.
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