Struct BatchLeastSquares

pub struct BatchLeastSquares<D: Dynamics, Trk: TrackerSensitivity<D::StateType, D::StateType>>
where
    D::StateType: Interpolatable + Add<OVector<f64, <D::StateType as State>::Size>, Output = D::StateType>,
    <D::StateType as State>::Size: DimName,
    <DefaultAllocator as Allocator<<D::StateType as State>::VecLength>>::Buffer<f64>: Send,
    <DefaultAllocator as Allocator<<D::StateType as State>::Size>>::Buffer<f64>: Copy,
    <DefaultAllocator as Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>>::Buffer<f64>: Copy,
    DefaultAllocator: Allocator<<D::StateType as State>::Size> + Allocator<<D::StateType as State>::VecLength> + Allocator<U1> + Allocator<U1, <D::StateType as State>::Size> + Allocator<<D::StateType as State>::Size, U1> + Allocator<U1, U1> + Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>,
{

    pub prop: Propagator<D>,
    pub devices: BTreeMap<String, Trk>,
    pub solver: BLSSolver,
    pub tolerance_pos_km: f64,
    pub max_iterations: usize,
    pub max_step: Duration,
    pub epoch_precision: Duration,
    pub lm_lambda_init: f64,
    pub lm_lambda_decrease: f64,
    pub lm_lambda_increase: f64,
    pub lm_lambda_min: f64,
    pub lm_lambda_max: f64,
    pub lm_use_diag_scaling: bool,
    pub almanac: Arc<Almanac>,
}

Configuration for the Batch Least Squares estimator

Fields

prop: Propagator<D>

Propagator used for the estimation reference trajectory

devices: BTreeMap<String, Trk>

Tracking devices

solver: BLSSolver

Solver method

tolerance_pos_km: f64

Convergence tolerance on the norm of the correction on position, in kilometers

max_iterations: usize

Maximum number of iterations

max_step: Duration

Maximum step size where the STM linearization is assumed correct (30 seconds is usually fine, but too large and info matrix could be singular)

epoch_precision: Duration

Precision of the measurement epoch when processing measurements.

lm_lambda_init: f64

Initial damping factor for Levenberg-Marquardt

lm_lambda_decrease: f64

Factor to decrease lambda by in LM

lm_lambda_increase: f64

Factor to increase lambda by in LM

lm_lambda_min: f64

Minimum value for LM lambda

lm_lambda_max: f64

Maximum value for LM lambda

lm_use_diag_scaling: bool

Use diagonal scaling (D = sqrt(diag(H^T W H))) in LM

almanac: Arc<Almanac>

Implementations

impl<D: Dynamics, Trk: TrackerSensitivity<D::StateType, D::StateType>> BatchLeastSquares<D, Trk>

where D::StateType: Interpolatable + Add<OVector<f64, <D::StateType as State>::Size>, Output = D::StateType>, <D::StateType as State>::Size: DimName, <DefaultAllocator as Allocator<<D::StateType as State>::VecLength>>::Buffer<f64>: Send, <DefaultAllocator as Allocator<<D::StateType as State>::Size>>::Buffer<f64>: Copy, <DefaultAllocator as Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>>::Buffer<f64>: Copy, DefaultAllocator: Allocator<<D::StateType as State>::Size> + Allocator<<D::StateType as State>::VecLength> + Allocator<U1> + Allocator<U1, <D::StateType as State>::Size> + Allocator<<D::StateType as State>::Size, U1> + Allocator<U1, U1> + Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>,

pub fn builder() -> BatchLeastSquaresBuilder<D, Trk, ((), (), (), (), (), (), (), (), (), (), (), (), (), ())>

Create a builder for building BatchLeastSquares. On the builder, call .prop(...), .devices(...), .solver(...)(optional), .tolerance_pos_km(...)(optional), .max_iterations(...)(optional), .max_step(...)(optional), .epoch_precision(...)(optional), .lm_lambda_init(...)(optional), .lm_lambda_decrease(...)(optional), .lm_lambda_increase(...)(optional), .lm_lambda_min(...)(optional), .lm_lambda_max(...)(optional), .lm_use_diag_scaling(...)(optional), .almanac(...) to set the values of the fields. Finally, call .build() to create the instance of BatchLeastSquares.

impl<D, Trk> BatchLeastSquares<D, Trk>

where D: Dynamics, Trk: TrackerSensitivity<D::StateType, D::StateType> + Clone, D::StateType: Interpolatable + Add<OVector<f64, <D::StateType as State>::Size>, Output = D::StateType> + Debug, <D::StateType as State>::Size: DimName, <DefaultAllocator as Allocator<<D::StateType as State>::VecLength>>::Buffer<f64>: Send, <DefaultAllocator as Allocator<<D::StateType as State>::Size>>::Buffer<f64>: Copy, <DefaultAllocator as Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>>::Buffer<f64>: Copy, DefaultAllocator: Allocator<<D::StateType as State>::Size> + Allocator<<D::StateType as State>::VecLength> + Allocator<U1> + Allocator<U1, <D::StateType as State>::Size> + Allocator<<D::StateType as State>::Size, U1> + Allocator<U1, U1> + Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>,

pub fn estimate( &self, initial_guess: D::StateType, arc: &TrackingDataArc, ) -> Result<BLSSolution<D::StateType>, ODError>

Processes a tracking data arc to estimate the state using Batch Least Squares.

Trait Implementations

impl<D: Clone + Dynamics, Trk: Clone + TrackerSensitivity<D::StateType, D::StateType>> Clone for BatchLeastSquares<D, Trk>

where D::StateType: Interpolatable + Add<OVector<f64, <D::StateType as State>::Size>, Output = D::StateType>, <D::StateType as State>::Size: DimName, <DefaultAllocator as Allocator<<D::StateType as State>::VecLength>>::Buffer<f64>: Send, <DefaultAllocator as Allocator<<D::StateType as State>::Size>>::Buffer<f64>: Copy, <DefaultAllocator as Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>>::Buffer<f64>: Copy, DefaultAllocator: Allocator<<D::StateType as State>::Size> + Allocator<<D::StateType as State>::VecLength> + Allocator<U1> + Allocator<U1, <D::StateType as State>::Size> + Allocator<<D::StateType as State>::Size, U1> + Allocator<U1, U1> + Allocator<<D::StateType as State>::Size, <D::StateType as State>::Size>,

fn clone(&self) -> BatchLeastSquares<D, Trk>

Returns a duplicate of the value.

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

Performs copy-assignment from source.