Abstract
Several filters are applied to the problem of state estimation from inertial measurements of reentry drag. This is a highly nonlinear problem of practical significance. It is found that a filter based on the technique of statistical linearization performs better than the extended Kalman in this application. This is believed to be the first application of the statistically linearized filter to a practical dynamics problem. A sensitivity analysis is performed to demonstrate the relative insensitivity of this filter to modeling errors and approximations.
Keywords
Kalman filterControl theory (sociology)ReentryLinearizationExtended Kalman filterFilter (signal processing)Nonlinear systemSensitivity (control systems)Computer scienceInertial frame of referenceInertial navigation systemMathematicsEngineeringPhysicsArtificial intelligenceElectronic engineering
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Publication Info
- Year
- 1981
- Type
- article
- Volume
- AES-17
- Issue
- 1
- Pages
- 54-61
- Citations
- 27
- Access
- Closed
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Cite This
James W. Austin,
Cornelius T. Leondes
(1981).
Statistically Linearized Estimation of Reentry Trajectories.
IEEE Transactions on Aerospace and Electronic Systems
, AES-17
(1)
, 54-61.
https://doi.org/10.1109/taes.1981.309036
Identifiers
- DOI
- 10.1109/taes.1981.309036