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gptkbp:instanceOf
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gptkb:algorithm
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gptkbp:abbreviation
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gptkb:UKF
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gptkbp:advantage
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better accuracy for nonlinear systems
no need for explicit Jacobian calculation
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gptkbp:alternativeTo
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gptkb:Extended_Kalman_filter
gptkb:Particle_filter
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gptkbp:application
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gptkb:navigation
aerospace
autonomous vehicles
robotics
sensor fusion
target tracking
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gptkbp:basedOn
|
unscented transform
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gptkbp:category
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recursive filter
Bayesian filter
state observer
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gptkbp:developedBy
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gptkb:Jeffrey_K._Uhlmann
gptkb:Simon_J._Julier
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gptkbp:field
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gptkb:estimation_theory
gptkb:signal_processing
control theory
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|
https://www.w3.org/2000/01/rdf-schema#label
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Unscented Kalman filter
|
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gptkbp:input
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Gaussian noise
nonlinear measurement model
nonlinear process model
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gptkbp:introducedIn
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1997
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gptkbp:limitation
|
assumes Gaussian noise
computationally more expensive than EKF
not optimal for highly non-Gaussian noise
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gptkbp:output
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error covariance
state estimate
|
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gptkbp:publishedIn
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gptkb:Proceedings_of_the_1997_American_Control_Conference
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gptkbp:relatedTo
|
gptkb:Extended_Kalman_filter
gptkb:Kalman_filter
|
|
gptkbp:usedFor
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nonlinear state estimation
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|
gptkbp:uses
|
sigma points
unscented transform
|
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gptkbp:bfsParent
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gptkb:Kalman_filter
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gptkbp:bfsLayer
|
4
|