UDKalmanFilter:
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Implements a Kalman filter using UD factorization.
First call
d = UDKalmanFilter( 'p to ud', p )
You need to add r, q, h, and x to d.
Then call
loop:
d = UDKalmanFilter( 'incorporate measurement', d, z )
d = UDKalmanFilter( 'propagate', d )
end
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Form:
d = UDKalmanFilter( action, d, z )
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Inputs
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action (1,:) Action to perform
d (1,1) Data structure
.u Upper triangular portion of the covariance matrix
.r Measurement noise scalar
.q State noise matrix
.h Measurement equation
.x State
.k Gain (computed)
z (n,1) Measurement(s)
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Outputs
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y (:) Depends on the action
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References: Bierman, G. J. (1977) Factorization Methods for Discrete
Sequential Estimation. Academic Press.
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Children:
