
Summary: An optimal batch estimator and smoother based on the minimum model error (MME) approach is developed for a three-axis stabilized spacecraft. The formulation is shown using only attitude sensors, e.g., three-axis magnetometers, sun sensors, star trackers. This algorithm accurately estimates the attitude of a spacecraft and substantially smoothes noise associated with attitude sensor measurements. The general functional form of the optimal estimation approach involves the solution of a nonlinear two-point-boundary-value problem that can be solved only by using computationally intense methods. A linearized solution also is shown that is computationally more efficient than methods that solve the general form.
Estimation and detection in stochastic control theory, attitude sensors, Application models in control theory, spacecraft, minimum model error approach, optimal estimation
Estimation and detection in stochastic control theory, attitude sensors, Application models in control theory, spacecraft, minimum model error approach, optimal estimation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 58 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
