Abstract
In radar systems, extended Kalman-Bucy filters (EKBFs) are used to estimate state vectors of objects in track. Filter models accounting for fundamental aerodynamic forces on reentry vehicles are well known. A general model structure accommodating the dynamics of reentry vehicles in both exoatmospheric and endoatmospheric flight is presented. The associated EKBFs for these various models are described and the resulting associated parameter estimation and identification problems are discussed. The effects of position, velocity, drag, and aerodynamic lift are described within a nested set of EKBF models.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Kalman filterAerodynamicsExtended Kalman filterControl theory (sociology)Lift (data mining)RadarComputer scienceSystem identificationEstimation theoryRadar trackerEngineeringAerospace engineeringAlgorithmData modelingArtificial intelligence
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Publication Info
- Year
- 1994
- Type
- article
- Volume
- 30
- Issue
- 2
- Pages
- 525-533
- Citations
- 96
- Access
- Closed
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Cite This
Paulo Costa
(1994).
Adaptive model architecture and extended Kalman-Bucy filters.
IEEE Transactions on Aerospace and Electronic Systems
, 30
(2)
, 525-533.
https://doi.org/10.1109/7.272275
Identifiers
- DOI
- 10.1109/7.272275