ADCS.estimators.attitude_estimators.attitude_AugmentedSRUKF module

Square-root unscented attitude estimator with augmented parameter blocks.

1. Construct the augmented square-root estimate

Validate the augmented tangent-state layout and store its covariance as an upper square-root factor.

2. Generate and propagate augmented sigma points

Synchronize each sigma point’s bias and disturbance parameters into EstimatedSatellite before nonlinear propagation.

3. Form square-root process statistics

Compute the weighted manifold mean and use QR/rank updates to incorporate augmented process noise into the predicted square-root covariance.

4. Predict sigma-point measurements

Form measurement deviations and state cross-covariances through the shared measurement stack.

5. Apply the square-root unscented correction

Compute the gain and update the physical and augmented state blocks while preserving the square-root covariance representation.

6. Retract the attitude and retain the augmented estimate

Keep the tangent chart and the square-root covariance for the next cycle.

class ADCS.estimators.attitude_estimators.attitude_AugmentedSRUKF.AugmentedSRUKF(satellite, state, *, dt, unmodeled_dynamics_psd=0.0, quaternion_mode='quaternion_vector', alpha=1.0, beta=2.0, kappa=0.0)[source]

Bases: SRUKF

SRUKF supporting sensor-bias and disturbance-parameter state blocks.

Parameters:

  • satellite (Any)

  • state (EstimatorState)

  • dt (float)

  • unmodeled_dynamics_psd (Any)

  • quaternion_mode (str)

  • alpha (float)

  • beta (float)

  • kappa (float)

supports_augmented_parameters = True