Struct BatchLeastSquares

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pub struct BatchLeastSquares<D: Dynamics, Trk: TrackerSensitivity<D::StateType, D::StateType>>{
Show 14 fields 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>,
}
Expand description

Configuration for the Batch Least Squares estimator

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§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§

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

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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.

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

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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§

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

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

Returns a copy of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more

Auto Trait Implementations§

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impl<D, Trk> Freeze for BatchLeastSquares<D, Trk>

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impl<D, Trk> RefUnwindSafe for BatchLeastSquares<D, Trk>

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impl<D, Trk> Send for BatchLeastSquares<D, Trk>

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impl<D, Trk> Sync for BatchLeastSquares<D, Trk>

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impl<D, Trk> Unpin for BatchLeastSquares<D, Trk>

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impl<D, Trk> UnwindSafe for BatchLeastSquares<D, Trk>

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