CovarianceUtilities.GetSigmaPointsFromCovariance(Variable, Variable, Variable, Array, Matrix, Matrix, Matrix) Method

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Description

Computes the values of the sigma points for all properties in the provided nominal state, using the arguments for the covariance, Alpha, Beta, and Kappa values.

 

Timing Precision Mode

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Method Signature

CovarianceUtilities.GetSigmaPointsFromCovariance(

Variable alpha,


Variable beta,


Variable kappa,


Array nominalState,


Matrix covariance,


Matrix sigmaPoints,


Matrix weights)

 

 

Arguments

alpha


Description:

The value for alpha to be used in the Scaled Unscented Transformation. Choosing Alpha << 1 reduces higher order effects when selecting sigma points.

Valid Range:

alpha > 0

 

 

beta


Description:

The value for beta to be used in the Scaled Unscented Transformation. Choosing Beta = 2 reflects a Gaussian distribution.

Valid Range:

beta > 0

 

 

kappa


Description:

The value for kappa to be used in the Scaled Unscented Transformation. Choosing Kappa >= 0 ensures the resulting covariance matrix will be positive semi-definite.

Valid Range:

kappa ≥ 0

 

 

nominalState


Description:

The nominal state associated with the covariance matrix.

 

 

covariance


Description:

The covariance matrix that describes the Gaussian distribution of uncertainty for the nominal state, from which the sigma points are computed.

 

 

sigmaPoints


Description:

The N x 2N+1 matrix that contains the sigma point values for all quantities in the provided nominal state.

 

 

weights


Description:

The 2*N+1 x 2 matrix of weighting factors (where column 1 is the weights for the mean and column 2 is the weights for covariance).

 

 

 

Syntax

CovarianceUtilities.GetSigmaPointsFromCovariance(myVariable1, myVariable2, myVariable3, myArray1, myMatrix1, myMatrix2, myMatrix3);

 

 

See also

CovarianceUtilities Object