Dynamic Estimation ================== .. automodule:: pytcl.dynamic_estimation :no-members: :no-undoc-members: Kalman Filters -------------- .. automodule:: pytcl.dynamic_estimation.kalman :no-members: :no-undoc-members: Linear Kalman Filter ^^^^^^^^^^^^^^^^^^^^ .. automodule:: pytcl.dynamic_estimation.kalman.linear :members: :undoc-members: :show-inheritance: Extended Kalman Filter ^^^^^^^^^^^^^^^^^^^^^^ .. automodule:: pytcl.dynamic_estimation.kalman.extended :members: :undoc-members: :show-inheritance: .. _constrained-ekf: Constrained Extended Kalman Filter ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ State-constrained filtering using Lagrange multiplier methods. Enforces equality and inequality constraints on the state estimate. .. automodule:: pytcl.dynamic_estimation.kalman.constrained :members: :undoc-members: :show-inheritance: Unscented & Cubature Kalman Filter ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. automodule:: pytcl.dynamic_estimation.kalman.unscented :members: :undoc-members: :show-inheritance: Square-Root Kalman Filters ^^^^^^^^^^^^^^^^^^^^^^^^^^ Numerically stable Kalman filter implementations that propagate the Cholesky factor of the covariance matrix. .. automodule:: pytcl.dynamic_estimation.kalman.square_root :members: :undoc-members: :show-inheritance: :exclude-members: SRKalmanState, SRKalmanPrediction, SRKalmanUpdate Interacting Multiple Model (IMM) Estimator ------------------------------------------ The IMM estimator handles systems with multiple possible dynamic modes. .. automodule:: pytcl.dynamic_estimation.imm :members: :undoc-members: :show-inheritance: Particle Filters ---------------- .. automodule:: pytcl.dynamic_estimation.particle_filters :no-members: :no-undoc-members: Bootstrap Particle Filter ^^^^^^^^^^^^^^^^^^^^^^^^^ .. automodule:: pytcl.dynamic_estimation.particle_filters.bootstrap :members: :undoc-members: :show-inheritance: .. _rbpf: Rao-Blackwellized Particle Filter ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Hybrid particle filter for systems with nonlinear and linear subsystems. Each particle maintains an independent Kalman filter for the linear components, reducing estimator variance. .. automodule:: pytcl.dynamic_estimation.rbpf :members: :undoc-members: :show-inheritance: Gaussian Sum Filter ------------------- .. automodule:: pytcl.dynamic_estimation.gaussian_sum_filter :members: :undoc-members: :show-inheritance: Information Filter ------------------ .. automodule:: pytcl.dynamic_estimation.information_filter :members: :undoc-members: :show-inheritance: H Infinity ---------- .. automodule:: pytcl.dynamic_estimation.kalman.h_infinity :members: :undoc-members: :show-inheritance: Matrix Utils ------------ .. automodule:: pytcl.dynamic_estimation.kalman.matrix_utils :members: :undoc-members: :show-inheritance: Sr Ukf ------ .. automodule:: pytcl.dynamic_estimation.kalman.sr_ukf :members: :undoc-members: :show-inheritance: Types ----- .. automodule:: pytcl.dynamic_estimation.kalman.types :members: :undoc-members: :show-inheritance: Ud Filter --------- .. automodule:: pytcl.dynamic_estimation.kalman.ud_filter :members: :undoc-members: :show-inheritance: Smoothers --------- .. automodule:: pytcl.dynamic_estimation.smoothers :members: :undoc-members: :show-inheritance: