Struct nyx_space::od::kalman::KF

pub struct KF<T, A, M>where
    A: DimName,
    M: DimName,
    T: State,
    DefaultAllocator: Allocator<f64, M> + Allocator<f64, <T as State>::Size> + Allocator<f64, <T as State>::VecLength> + Allocator<f64, A> + Allocator<f64, M, M> + Allocator<f64, M, <T as State>::Size> + Allocator<f64, <T as State>::Size, <T as State>::Size> + Allocator<f64, A, A> + Allocator<f64, <T as State>::Size, A> + Allocator<f64, A, <T as State>::Size> + Allocator<usize, <T as State>::Size> + Allocator<usize, <T as State>::Size, <T as State>::Size>,{
    pub prev_estimate: KfEstimate<T>,
    pub measurement_noise: OMatrix<f64, M, M>,
    pub process_noise: Vec<SNC<A>>,
    pub ekf: bool,
    /* private fields */
}

Defines both a Classical and an Extended Kalman filter (CKF and EKF) S: State size (not propagated vector size) A: Acceleration size (for SNC) M: Measurement size (used for the sensitivity matrix) T: Type of state P: Propagated vector size

Fields

prev_estimate: KfEstimate<T>

The previous estimate used in the KF computations.

measurement_noise: OMatrix<f64, M, M>

Sets the Measurement noise (usually noted R)

process_noise: Vec<SNC<A>>

A sets of process noise (usually noted Q), must be ordered chronologically

ekf: bool

Determines whether this KF should operate as a Conventional/Classical Kalman filter or an Extended Kalman Filter. Recall that one should switch to an Extended KF only once the estimate is good (i.e. after a few good measurement updates on a CKF).

Implementations

impl<T, A, M> KF<T, A, M>where A: DimName, M: DimName, T: State, DefaultAllocator: Allocator<f64, M> + Allocator<f64, <T as State>::Size> + Allocator<f64, <T as State>::VecLength> + Allocator<f64, A> + Allocator<f64, M, M> + Allocator<f64, M, <T as State>::Size> + Allocator<f64, <T as State>::Size, M> + Allocator<f64, <T as State>::Size, <T as State>::Size> + Allocator<f64, A, A> + Allocator<f64, <T as State>::Size, A> + Allocator<f64, A, <T as State>::Size> + Allocator<usize, <T as State>::Size> + Allocator<usize, <T as State>::Size, <T as State>::Size>,

pub fn new( initial_estimate: KfEstimate<T>, process_noise: SNC<A>, measurement_noise: OMatrix<f64, M, M> ) -> Self

Initializes this KF with an initial estimate, measurement noise, and one process noise

pub fn with_sncs( initial_estimate: KfEstimate<T>, process_noises: Vec<SNC<A>>, measurement_noise: OMatrix<f64, M, M> ) -> Self

Initializes this KF with an initial estimate, measurement noise, and several process noise WARNING: SNCs MUST be ordered chronologically! They will be selected automatically by walking the list of SNCs backward until one can be applied!

impl<T, M> KF<T, U3, M>where M: DimName, T: State, DefaultAllocator: Allocator<f64, M> + Allocator<f64, <T as State>::Size> + Allocator<f64, <T as State>::VecLength> + Allocator<f64, M, M> + Allocator<f64, M, <T as State>::Size> + Allocator<f64, <T as State>::Size, M> + Allocator<f64, <T as State>::Size, <T as State>::Size> + Allocator<f64, U3, U3> + Allocator<f64, <T as State>::Size, U3> + Allocator<f64, U3, <T as State>::Size> + Allocator<usize, <T as State>::Size> + Allocator<usize, <T as State>::Size, <T as State>::Size>,

pub fn no_snc( initial_estimate: KfEstimate<T>, measurement_noise: OMatrix<f64, M, M> ) -> Self

Initializes this KF without SNC

Trait Implementations

impl<T, A, M> Clone for KF<T, A, M>where A: DimName + Clone, M: DimName + Clone, T: State + Clone, DefaultAllocator: Allocator<f64, M> + Allocator<f64, <T as State>::Size> + Allocator<f64, <T as State>::VecLength> + Allocator<f64, A> + Allocator<f64, M, M> + Allocator<f64, M, <T as State>::Size> + Allocator<f64, <T as State>::Size, <T as State>::Size> + Allocator<f64, A, A> + Allocator<f64, <T as State>::Size, A> + Allocator<f64, A, <T as State>::Size> + Allocator<usize, <T as State>::Size> + Allocator<usize, <T as State>::Size, <T as State>::Size>,

fn clone(&self) -> KF<T, A, M>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T, A, M> Debug for KF<T, A, M>where A: DimName + Debug, M: DimName + Debug, T: State + Debug, DefaultAllocator: Allocator<f64, M> + Allocator<f64, <T as State>::Size> + Allocator<f64, <T as State>::VecLength> + Allocator<f64, A> + Allocator<f64, M, M> + Allocator<f64, M, <T as State>::Size> + Allocator<f64, <T as State>::Size, <T as State>::Size> + Allocator<f64, A, A> + Allocator<f64, <T as State>::Size, A> + Allocator<f64, A, <T as State>::Size> + Allocator<usize, <T as State>::Size> + Allocator<usize, <T as State>::Size, <T as State>::Size>,

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

Formats the value using the given formatter.

impl<T, A, M> Filter<T, A, M> for KF<T, A, M>where A: DimName, M: DimName, T: State, DefaultAllocator: Allocator<f64, M> + Allocator<f64, <T as State>::Size> + Allocator<f64, <T as State>::VecLength> + Allocator<f64, A> + Allocator<f64, M, M> + Allocator<f64, M, <T as State>::Size> + Allocator<f64, <T as State>::Size, M> + Allocator<f64, <T as State>::Size, <T as State>::Size> + Allocator<f64, A, A> + Allocator<f64, <T as State>::Size, A> + Allocator<f64, A, <T as State>::Size> + Allocator<usize, <T as State>::Size> + Allocator<usize, <T as State>::Size, <T as State>::Size>,

fn previous_estimate(&self) -> &Self::Estimate

Returns the previous estimate

fn update_h_tilde(&mut self, h_tilde: OMatrix<f64, M, <T as State>::Size>)

Update the sensitivity matrix (or “H tilde”). This function must be called prior to each call to measurement_update.

fn time_update(&mut self, nominal_state: T) -> Result<Self::Estimate, NyxError>

Computes a time update/prediction (i.e. advances the filter estimate with the updated STM).

May return a FilterError if the STM was not updated.

fn measurement_update( &mut self, nominal_state: T, real_obs: &OVector<f64, M>, computed_obs: &OVector<f64, M> ) -> Result<(Self::Estimate, Residual<M>), NyxError>

Computes the measurement update with a provided real observation and computed observation.

May return a FilterError if the STM or sensitivity matrices were not updated.

fn set_process_noise(&mut self, snc: SNC<A>)

Overwrites all of the process noises to the one provided

type Estimate = KfEstimate<T>

fn measurement_noise(&self, _epoch: Epoch) -> &OMatrix<f64, M, M>

Returns the measurement noise used at this given epoch

fn set_previous_estimate(&mut self, est: &Self::Estimate)

Set the previous estimate

fn is_extended(&self) -> bool

Returns whether the filter is an extended filter (e.g. EKF)

fn set_extended(&mut self, status: bool)

Sets the filter to be extended or not depending on the value of status