Struct nyx_space::od::estimate::KfEstimate [−][src]
pub struct KfEstimate<T: State> where
DefaultAllocator: Allocator<f64, <T as State>::Size> + Allocator<f64, <T as State>::Size, <T as State>::Size> + Allocator<usize, <T as State>::Size> + Allocator<usize, <T as State>::Size, <T as State>::Size>, { pub nominal_state: T, pub state_deviation: VectorN<f64, <T as State>::Size>, pub covar: MatrixMN<f64, <T as State>::Size, <T as State>::Size>, pub covar_bar: MatrixMN<f64, <T as State>::Size, <T as State>::Size>, pub predicted: bool, pub stm: MatrixMN<f64, <T as State>::Size, <T as State>::Size>, pub epoch_fmt: EpochFormat, pub covar_fmt: CovarFormat, }
Expand description
Kalman filter Estimate
Fields
nominal_state: T
The estimated state
state_deviation: VectorN<f64, <T as State>::Size>
The state deviation
covar: MatrixMN<f64, <T as State>::Size, <T as State>::Size>
The Covariance of this estimate
covar_bar: MatrixMN<f64, <T as State>::Size, <T as State>::Size>
The predicted covariance of this estimate
predicted: bool
Whether or not this is a predicted estimate from a time update, or an estimate from a measurement
stm: MatrixMN<f64, <T as State>::Size, <T as State>::Size>
The STM used to compute this Estimate
epoch_fmt: EpochFormat
The Epoch format upon serialization
covar_fmt: CovarFormat
The covariance format upon serialization
Implementations
Trait Implementations
An empty estimate. This is useful if wanting to store an estimate outside the scope of a filtering loop.
The nominal state as reported by the filter dynamics
The state deviation as computed by the filter.
The Covariance of this estimate. Will return the predicted covariance if this is a time update/prediction.
The predicted covariance of this estimate from the time update
Whether or not this is a predicted estimate from a time update, or an estimate from a measurement
The STM used to compute this Estimate
The Epoch format upon serialization
The covariance format upon serialization
Sets the state deviation.
Sets the Covariance of this estimate
Returns whether this estimate is within some bound The 68-95-99.7 rule is a good way to assess whether the filter is operating normally Read more
Returns whether this estimate is within 3 sigma, which represent 99.7% for a Normal distribution
Returns the header
Returns the default header
Returns the nominal state as computed by the dynamics
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
This method tests for !=
.
Auto Trait Implementations
impl<T> !RefUnwindSafe for KfEstimate<T>
impl<T> !Send for KfEstimate<T>
impl<T> !Sync for KfEstimate<T>
impl<T> !Unpin for KfEstimate<T>
impl<T> !UnwindSafe for KfEstimate<T>
Blanket Implementations
Mutably borrows from an owned value. Read more
type Output = T
type Output = T
Should always be Self
The inverse inclusion map: attempts to construct self
from the equivalent element of its
superset. Read more
pub fn is_in_subset(&self) -> bool
pub fn is_in_subset(&self) -> bool
Checks if self
is actually part of its subset T
(and can be converted to it).
pub fn to_subset_unchecked(&self) -> SS
pub fn to_subset_unchecked(&self) -> SS
Use with care! Same as self.to_subset
but without any property checks. Always succeeds.
pub fn from_subset(element: &SS) -> SP
pub fn from_subset(element: &SS) -> SP
The inclusion map: converts self
to the equivalent element of its superset.
pub fn vzip(self) -> V