Expand description
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
An error
A Kalman filter with no control inputs, a linear process model and linear
observation model
State and covariance pair for a given estimate
Enums
Specifies the approach used for updating the covariance matrix
The kinds of errors
Traits
An observation model, potentially non-linear.
A linear model of process dynamics with no control inputs