navlie.lib.models.LinearMeasurement¶

class navlie.lib.models.LinearMeasurement(C: ndarray, R: ndarray)¶

A generic linear measurement model of the form

\[\mathbf{y} = \mathbf{C} \mathbf{x} + \mathbf{v}\]

where \(\mathbf{C}\) is a matrix and \(\mathbf{v}\) is a zero-mean Gaussian noise vector with covariance \(\mathbf{R}\).

This class is comptabile with VectorState.

Parameters:

evaluate(x: VectorState) → ndarray¶: Evaluates the measurement model \(\mathbf{g}(\mathcal{X})\).

jacobian(x: VectorState) → ndarray¶: Evaluates the measurement model Jacobian with respect to the state.

\[\mathbf{G} = \frac{D \mathbf{g}(\mathcal{X})}{D \mathcal{X}}\]

covariance(x: VectorState) → ndarray¶: Returns the covariance \(\mathbf{R}\) associated with additive Gaussian noise.

evaluate_with_jacobian(x: State) → Tuple[ndarray, ndarray]¶: Evaluates the measurement model and simultaneously returns the Jacobian as its second output argument. This is useful to override for performance reasons when the model evaluation and Jacobian have a lot of common calculations, and it is more efficient to calculate them in the same function call.

jacobian_fd(x: State, step_size=1e-06)¶: Calculates the model jacobian with finite difference.

navlie.lib.models.InvariantPointRelativePosition

navlie.lib.models.Magnetometer