Crate adskalman

Kalman filter and Rauch-Tung-Striebel smoothing implementation

Characteristics:

• Uses the nalgebra crate for math.
• Supports no_std to facilitate running on embedded microcontrollers.
• Includes various methods of computing the covariance matrix on the update step.
• Examples included.
• Strong typing used to ensure correct matrix dimensions at compile time.

Throughout the library, the generic type SS means “state size” and OS is “observation size”. These refer to the number of dimensions of the state vector and observation vector, respectively.

Structs

• KalmanFilterNoControl
  A Kalman filter with no control inputs, a linear process model and linear observation model
• StateAndCovariance
  State and covariance pair for a given estimate

Enums

• CovarianceUpdateMethod
  Specifies the approach used for updating the covariance matrix
• Error
  An Kalman filter error

Traits

• ObservationModel
  An observation model, potentially non-linear.
• TransitionModelLinearNoControl
  A linear model of process dynamics with no control inputs