Kalman filter and Rauch-Tung-Striebel smoothing implementation
- Uses the nalgebra crate for math.
no_stdto 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
“observation size”. These refer to the number of dimensions of the state
vector and observation vector, respectively.
A Kalman filter with no control inputs, a linear process model and linear observation model
State and covariance pair for a given estimate
Specifies the approach used for updating the covariance matrix
The kinds of errors
An observation model, potentially non-linear.
A linear model of process dynamics with no control inputs