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gptkbp:instanceOf
|
gptkb:algorithm
gptkb:state_estimation_method
|
|
gptkbp:alternativeTo
|
gptkb:Unscented_Kalman_Filter
Particle Filter
|
|
gptkbp:appliesTo
|
gptkb:navigation
gptkb:signal_processing
control systems
robotics
|
|
gptkbp:assumes
|
gptkb:Markov_chain
Gaussian noise
differentiable models
|
|
gptkbp:basedOn
|
gptkb:Kalman_Filter
|
|
gptkbp:category
|
recursive filter
Bayesian filter
|
|
gptkbp:developedBy
|
1960s
|
|
gptkbp:field
|
gptkb:navigation
gptkb:signal_processing
control theory
robotics
|
|
gptkbp:form
|
gptkb:partial_differential_equations
gptkb:probability_theory
linear algebra
matrix calculus
|
|
gptkbp:input
|
nonlinear measurement model
nonlinear process model
|
|
gptkbp:limitation
|
approximation errors
divergence in highly nonlinear systems
|
|
gptkbp:output
|
error covariance
state estimate
|
|
gptkbp:relatedTo
|
gptkb:Kalman_Filter
gptkb:Ensemble_Kalman_Filter
gptkb:Unscented_Kalman_Filter
Particle Filter
|
|
gptkbp:requires
|
Jacobian matrix
|
|
gptkbp:step
|
prediction
update
linearization
covariance update
state correction
|
|
gptkbp:usedFor
|
gptkb:SLAM
autonomous vehicles
attitude estimation
sensor fusion
target tracking
econometrics
aerospace applications
mobile robotics
GPS navigation
|
|
gptkbp:usedIn
|
nonlinear systems
|
|
gptkbp:uses
|
linearization
|
|
gptkbp:bfsParent
|
gptkb:EKF-SLAM
|
|
gptkbp:bfsLayer
|
7
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Extended Kalman Filter
|