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gptkbp:instanceOf
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gptkb:state_estimation_algorithm
gptkb:nonlinear_filter
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|
gptkbp:advantage
|
no need for explicit Jacobian calculation
better accuracy for highly nonlinear systems
|
|
gptkbp:application
|
gptkb:signal_processing
aerospace
autonomous vehicles
biomedical engineering
finance
|
|
gptkbp:basedOn
|
Unscented Transform
|
|
gptkbp:contrastsWith
|
gptkb:Extended_Kalman_Filter
|
|
gptkbp:developedBy
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gptkb:Jeffrey_K._Uhlmann
gptkb:Simon_J._Julier
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gptkbp:input
|
nonlinear measurement model
nonlinear process model
|
|
gptkbp:introducedIn
|
1997
|
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gptkbp:output
|
error covariance
state estimate
|
|
gptkbp:relatedTo
|
gptkb:Kalman_Filter
gptkb:Ensemble_Kalman_Filter
Particle Filter
|
|
gptkbp:supportsAlgorithm
|
Bayesian filter
recursive
|
|
gptkbp:usedFor
|
gptkb:navigation
control systems
robotics
nonlinear state estimation
sensor fusion
|
|
gptkbp:uses
|
sigma points
weighted mean and covariance
|
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gptkbp:bfsParent
|
gptkb:Extended_Kalman_Filter
gptkb:Kalman_Filter
|
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gptkbp:bfsLayer
|
8
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Unscented Kalman Filter
|