Struct ObservationModel2D 

pub struct ObservationModel2D<R: RealField + Copy> { /* private fields */ }

Implementations

impl<R: RealField + Copy> ObservationModel2D<R>

pub fn new(observation_noise_covariance: OMatrix<R, U2, U2>) -> Self

Trait Implementations

impl<R: Debug + RealField + Copy> Debug for ObservationModel2D<R>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<R: RealField + Copy> ObservationModel<R, Const<4>, Const<2>> for ObservationModel2D<R>

where DefaultAllocator: Allocator<U4, U4> + Allocator<U4> + Allocator<U2, U4> + Allocator<U4, U2> + Allocator<U2, U2> + Allocator<U2>, U2: DimMin<U2, Output = U2>,

fn H(&self) -> &OMatrix<R, U2, U4>

Get the observation matrix, H.

fn HT(&self) -> &OMatrix<R, U4, U2>

Get the transpose of the observation matrix, HT.

fn R(&self) -> &OMatrix<R, U2, U2>

Get the observation noise covariance, R.

fn predict_observation(&self, state: &OVector<R, U4>) -> OVector<R, U2>

For a given state, predict the observation.

fn update( &self, prior: &StateAndCovariance<R, SS>, observation: &Matrix<R, OS, Const<1>, <DefaultAllocator as Allocator<OS>>::Buffer<R>>, covariance_method: CovarianceUpdateMethod, ) -> Result<StateAndCovariance<R, SS>, Error>

Given prior state and observation, estimate the posterior state.