BatchLSEstimator (ORbit Extrapolation KIT 9.2 API)

java.lang.Object
- org.orekit.estimation.leastsquares.BatchLSEstimator

```
public class BatchLSEstimator
extends Object
```
Least squares estimator for orbit determination.

Since:

8.0

Author:

Luc Maisonobe

Constructor Summary

Constructors
Constructor Description

BatchLSEstimator(LeastSquaresOptimizer optimizer, NumericalPropagatorBuilder... propagatorBuilder)
Simple constructor.

Constructors
Constructor	Description
`BatchLSEstimator(LeastSquaresOptimizer optimizer, NumericalPropagatorBuilder... propagatorBuilder)`	Simple constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`void`	`addMeasurement(ObservedMeasurement<?> measurement)`	Add a measurement.
`NumericalPropagator[]`	`estimate()`	Estimate the orbital, propagation and measurements parameters.
`int`	`getEvaluationsCount()`	Get the number of evaluations used for last estimation.
`int`	`getIterationsCount()`	Get the number of iterations used for last estimation.
`Map<ObservedMeasurement<?>,EstimatedMeasurement<?>>`	`getLastEstimations()`	Get the last estimations performed.
`ParameterDriversList`	`getMeasurementsParametersDrivers(boolean estimatedOnly)`	Get the measurements parameters supported by this estimator (including measurements and modifiers).
`LeastSquaresOptimizer.Optimum`	`getOptimum()`	Get the optimum found.
`ParameterDriversList`	`getOrbitalParametersDrivers(boolean estimatedOnly)`	Get the orbital parameters supported by this estimator.
`RealMatrix`	`getPhysicalCovariances(double threshold)`	Get the covariances matrix in space flight dynamics physical units.
`ParameterDriversList`	`getPropagatorParametersDrivers(boolean estimatedOnly)`	Get the propagator parameters supported by this estimator.
`void`	`setMaxEvaluations(int maxEvaluations)`	Set the maximum number of model evaluations.
`void`	`setMaxIterations(int maxIterations)`	Set the maximum number of iterations.
`void`	`setObserver(BatchLSObserver observer)`	Set an observer for iterations.
`void`	`setParametersConvergenceThreshold(double parametersConvergenceThreshold)`	Set convergence threshold.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - BatchLSEstimator
```
public BatchLSEstimator(LeastSquaresOptimizer optimizer,
                        NumericalPropagatorBuilder... propagatorBuilder)
                 throws OrekitException
```
    Simple constructor.
    If multiple propagator builders are set up, the orbits of several spacecrafts will be used simultaneously. This is useful if the propagators share some model or measurements parameters (typically pole motion, prime meridian correction or ground stations positions).
    
    Setting up multiple propagator builders is also useful when inter-satellite measurements are used, even if only one of the orbit is estimated and the other ones are fixed. This is typically used when very high accuracy GNSS measurements are needed and the navigation bulletins are not considered accurate enough and the navigation constellation must be propagated numerically.
    
    Parameters:
    
    optimizer - solver for least squares problem
    
    propagatorBuilder - builders to use for propagation
    
    Throws:
    
    OrekitException - if some propagator parameter cannot be retrieved
- Method Detail
  - setObserver
```
public void setObserver(BatchLSObserver observer)
```
    Set an observer for iterations.
    
    Parameters:
    
    observer - observer to be notified at the end of each iteration
  - addMeasurement
```
public void addMeasurement(ObservedMeasurement<?> measurement)
                    throws OrekitException
```
    Add a measurement.
    
    Parameters:
    
    measurement - measurement to add
    
    Throws:
    
    OrekitException - if the measurement has a parameter that is already used
  - setMaxIterations
```
public void setMaxIterations(int maxIterations)
```
    Set the maximum number of iterations.
    The iterations correspond to the top level iterations of the least squares optimizer.
    
    Parameters:
    
    maxIterations - maxIterations maximum number of iterations
    
    See Also:
    
    setMaxEvaluations(int), getIterationsCount()
  - setMaxEvaluations
```
public void setMaxEvaluations(int maxEvaluations)
```
    Set the maximum number of model evaluations.
    The evaluations correspond to the orbit propagations and measurements estimations performed with a set of estimated parameters.
    
    For Gauss-Newton optimizer there is one evaluation at each iteration, so the maximum numbers may be set to the same value. For Levenberg-Marquardt optimizer, there can be several evaluations at some iterations (typically for the first couple of iterations), so the maximum number of evaluations may be set to a higher value than the maximum number of iterations.
    
    Parameters:
    
    maxEvaluations - maximum number of model evaluations
    
    See Also:
    
    setMaxIterations(int), getEvaluationsCount()
  - getOrbitalParametersDrivers
```
public ParameterDriversList getOrbitalParametersDrivers(boolean estimatedOnly)
                                                 throws OrekitException
```
    Get the orbital parameters supported by this estimator.
    If there are more than one propagator builder, then the names of the drivers have an index marker in square brackets appended to them in order to distinguish the various orbits. So for example with one builder generating Keplerian orbits the names would be simply "a", "e", "i"... but if there are several builders the names would be "a[0]", "e[0]", "i[0]"..."a[1]", "e[1]", "i[1]"...
    
    Parameters:
    
    estimatedOnly - if true, only estimated parameters are returned
    
    Returns:
    
    orbital parameters supported by this estimator
    
    Throws:
    
    OrekitException - if different parameters have the same name
  - getPropagatorParametersDrivers
```
public ParameterDriversList getPropagatorParametersDrivers(boolean estimatedOnly)
                                                    throws OrekitException
```
    Get the propagator parameters supported by this estimator.
    
    Parameters:
    
    estimatedOnly - if true, only estimated parameters are returned
    
    Returns:
    
    propagator parameters supported by this estimator
    
    Throws:
    
    OrekitException - if different parameters have the same name
  - getMeasurementsParametersDrivers
```
public ParameterDriversList getMeasurementsParametersDrivers(boolean estimatedOnly)
                                                      throws OrekitException
```
    Get the measurements parameters supported by this estimator (including measurements and modifiers).
    
    Parameters:
    
    estimatedOnly - if true, only estimated parameters are returned
    
    Returns:
    
    measurements parameters supported by this estimator
    
    Throws:
    
    OrekitException - if different parameters have the same name
  - setParametersConvergenceThreshold
```
public void setParametersConvergenceThreshold(double parametersConvergenceThreshold)
```
    Set convergence threshold.
    The convergence used for estimation is based on the estimated parameters normalized values. Convergence is considered to have been reached when the difference between previous and current normalized value is less than the convergence threshold for all parameters. The same value is used for all parameters since they are normalized and hence dimensionless.
    
    Normalized values are computed as (current - reference)/scale, so convergence is reached when the following condition holds for all estimated parameters: |current[i] - previous[i]| <= threshold * scale[i]
    
    So the convergence threshold specified here can be considered as a multiplication factor applied to scale. Since for all parameters the scale is often small (typically about 1 m for orbital positions for example), then the threshold should not be too small. A value of 10⁻³ is often quite accurate.
    
    Parameters:
    
    parametersConvergenceThreshold - convergence threshold on normalized parameters (dimensionless, related to parameters scales)
    
    See Also:
    
    EvaluationRmsChecker
  - estimate
```
public NumericalPropagator[] estimate()
                               throws OrekitException
```
    Estimate the orbital, propagation and measurements parameters.
    The initial guess for all parameters must have been set before calling this method using getOrbitalParametersDrivers(boolean), getPropagatorParametersDrivers(boolean), and getMeasurementsParametersDrivers(boolean) and then setting the values of the parameters.
    
    For parameters whose reference date has not been set to a non-null date beforehand (i.e. the parameters for which ParameterDriver.getReferenceDate() returns null, a default reference date will be set automatically at the start of the estimation to the initial orbit date of the first propagator builder. For parameters whose reference date has been set to a non-null date, this reference date is untouched.
    
    After this method returns, the estimated parameters can be retrieved using getOrbitalParametersDrivers(boolean), getPropagatorParametersDrivers(boolean), and getMeasurementsParametersDrivers(boolean) and then getting the values of the parameters.
    
    As a convenience, the method also returns a fully configured and ready to use propagator set up with all the estimated values.
    
    For even more in-depth information, the getOptimum() method provides detailed elements (covariance matrix, estimated parameters standard deviation, weighted Jacobian, RMS, χ², residuals and more).
    
    Returns:
    
    propagators configured with estimated orbits as initial states, and all propagators estimated parameters also set
    
    Throws:
    
    OrekitException - if there is a conflict in parameters names or if orbit cannot be determined
  - getLastEstimations
```
public Map<ObservedMeasurement<?>,EstimatedMeasurement<?>> getLastEstimations()
```
    Get the last estimations performed.
    
    Returns:
    
    last estimations performed
  - getOptimum
```
public LeastSquaresOptimizer.Optimum getOptimum()
```
    Get the optimum found.
    The LeastSquaresOptimizer.Optimum object contains detailed elements (covariance matrix, estimated parameters standard deviation, weighted Jacobian, RMS, χ², residuals and more).
    
    Beware that the returned object is the raw view from the underlying mathematical library. At this ral level, parameters have normalized values whereas the space flight parameters have physical values with their units. So there are scaling factors to apply when using these elements.
    
    Returns:
    
    optimum found after last call to estimate()
  - getPhysicalCovariances
```
public RealMatrix getPhysicalCovariances(double threshold)
                                  throws OrekitException
```
    Get the covariances matrix in space flight dynamics physical units.
    This method retrieve the covariances from the [@link optimum and applies the scaling factors to it in order to convert it from raw normalized values back to physical values.
    
    Parameters:
    
    threshold - threshold to identify matrix singularity
    
    Returns:
    
    covariances matrix in space flight dynamics physical units
    
    Throws:
    
    OrekitException - if the covariance matrix cannot be computed (singular problem).
    
    Since:
    
    9.1
  - getIterationsCount
```
public int getIterationsCount()
```
    Get the number of iterations used for last estimation.
    
    Returns:
    
    number of iterations used for last estimation
    
    See Also:
    
    setMaxIterations(int)
  - getEvaluationsCount
```
public int getEvaluationsCount()
```
    Get the number of evaluations used for last estimation.
    
    Returns:
    
    number of evaluations used for last estimation
    
    See Also:
    
    setMaxEvaluations(int)

Class BatchLSEstimator

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

BatchLSEstimator

Method Detail

setObserver

addMeasurement

setMaxIterations

setMaxEvaluations

getOrbitalParametersDrivers

getPropagatorParametersDrivers

getMeasurementsParametersDrivers

setParametersConvergenceThreshold

estimate

getLastEstimations

getOptimum

getPhysicalCovariances

getIterationsCount

getEvaluationsCount