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Orbital Mechanics Seminar
Attitude Estimation Employing Common Frame Error Representations
3:30 pm
WRW 113
Estimating the attitude of a rigid body has applications to many systems, including spacecraft, inertial navigation of aerial vehicles (both piloted and uninhabited), underwater vehicles, and robotic systems, to name a few. The first known algorithm for attitude estimation dates back to 1970, which is based on the famous quasi-linear (extended) Kalman filter algorithm. This algorithm has been the workhorse for most systems that require attitude knowledge. Due to the inherent nonlinearities associated with attitude estimation, numerous nonlinear estimation techniques have been developed since that time. Some have shown global, or near-global, convergence while others focus on robust methods to handle model errors or non-Gaussian characteristics. Much less attention has been given to the problem of estimating vector state coordinates with respect to the attitude state coordinate frame. This work presents a new error definition in which vector error quantities are defined using elements expressed in a common frame. It is claimed here that the new error definition is more grounded theoretically than the usual error definition used by all other techniques. Examples in spacecraft attitude estimation are given to show the advantage of the new error definition over the standard error definition.
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