grss.prop.prop_unscented.SigmaPoints#

class grss.prop.prop_unscented.SigmaPoints(x_dict, cov, sp_type, alpha=None, beta=None, kappa=None, sqrt_func=None)#

Bases: object

Class for representing sigma points for the unscented transformation.

__init__(x_dict, cov, sp_type, alpha=None, beta=None, kappa=None, sqrt_func=None)#

Initialize a sigma point object.

Parameters:

x_dict (dict) – solution dictionary containing cometary/cartesian elements
cov (numpy.ndarray) – covariance matrix of the solution
sp_type (str) – type of sigma point. Choose from merwe or julier
alpha (float) – scaling parameter for sigma points
beta (float) – scaling parameter for sigma points
kappa (float) – scaling parameter for sigma points
sqrt_func (function) – function to compute the square root of the covariance matrix

Methods

`__init__`(x_dict, cov, sp_type[, alpha, ...])	Initialize a sigma point object.
`reconstruct`(transformed_sigma_points)	Reconstruct the mean and covariance from transformed sigma points.

reconstruct(transformed_sigma_points)#

Reconstruct the mean and covariance from transformed sigma points.

Parameters:

transformed_sigma_points (np.ndarray) – transformed sigma points

Returns:

grss.prop.prop_unscented.SigmaPoints