Class SingleParameterFitter

java.lang.Object
org.orekit.frames.SingleParameterFitter
All Implemented Interfaces:
Serializable

public class SingleParameterFitter extends Object implements Serializable
Fitter for one Earth Orientation Parameter.
Since:
12.0
Author:
Luc Maisonobe
See Also:
  • Field Details

    • SUN_PULSATION

      public static final double SUN_PULSATION
      Sun pulsation, one year period.
      See Also:
    • MOON_DRACONIC_PULSATION

      public static final double MOON_DRACONIC_PULSATION
      Moon pulsation (one Moon draconic period).
      See Also:
  • Constructor Details

  • Method Details

    • fit

      public SecularAndHarmonic fit(EOPHistory rawHistory, ToDoubleFunction<EOPEntry> extractor)
      Perform secular and harmonic fitting.
      Parameters:
      rawHistory - EOP history to fit
      extractor - extractor for Earth Orientation Parameter
      Returns:
      configured fitter
    • createDefaultDut1FitterShortTermPrediction

      public static SingleParameterFitter createDefaultDut1FitterShortTermPrediction()
      Create fitter with default parameters adapted for fitting orientation parameters dUT1 and LOD for short term prediction.

      The main difference between these settings and the settings for long prediction is the much smaller \(\tau\). This means more weight is set to the points at the end of the history, hence forcing the fitted prediction model to be closer to these points, hence the prediction error to be smaller just after raw history end. On the other hand, this implies that the model will diverge on long term. These settings are intended when prediction is used for at most 5 days after raw EOP end.

      Returns:
      fitter with default configuration for orientation parameters dUT1 and LOD
      See Also:
    • createDefaultDut1FitterLongTermPrediction

      public static SingleParameterFitter createDefaultDut1FitterLongTermPrediction()
      Create fitter with default parameters adapted for fitting orientation parameters dUT1 and LOD for long term prediction.

      The main difference between these settings and the settings for short prediction is the much larger \(\tau\). This means weight is spread throughout history, hence forcing the fitted prediction model to be remain very stable on the long term. On the other hand, this implies that the model will start with already a much larger error just after raw history end. These settings are intended when prediction is used for 5 days after raw EOP end or more.

      Returns:
      fitter with default configuration for orientation parameters dUT1 and LOD
      See Also:
    • createDefaultPoleFitterShortTermPrediction

      public static SingleParameterFitter createDefaultPoleFitterShortTermPrediction()
      Create fitter with default parameters adapted for fitting pole parameters Xp and Yp for long term prediction.

      The main difference between these settings and the settings for long prediction is the much smaller \(\tau\). This means more weight is set to the points at the end of the history, hence forcing the fitted prediction model to be closer to these points, hence the prediction error to be smaller just after raw history end. On the other hand, this implies that the model will diverge on long term. These settings are intended when prediction is used for at most 5 days after raw EOP end.

      Returns:
      fitter with default configuration for pole parameters Xp and Yp
    • createDefaultPoleFitterLongTermPrediction

      public static SingleParameterFitter createDefaultPoleFitterLongTermPrediction()
      Create fitter with default parameters adapted for fitting pole parameters Xp and Yp for long term prediction.

      The main difference between these settings and the settings for short prediction is the much larger \(\tau\). This means weight is spread throughout history, hence forcing the fitted prediction model to be remain very stable on the long term. On the other hand, this implies that the model will start with already a much larger error just after raw history end. These settings are intended when prediction is used for 5 days after raw EOP end or more.

      Returns:
      fitter with default configuration for pole parameters Xp and Yp
    • createDefaultNutationFitterShortTermPrediction

      public static SingleParameterFitter createDefaultNutationFitterShortTermPrediction()
      Create fitter with default parameters adapted for fitting nutation parameters dx and dy for long term prediction.

      The main difference between these settings and the settings for long prediction is the much smaller \(\tau\). This means more weight is set to the points at the end of the history, hence forcing the fitted prediction model to be closer to these points, hence the prediction error to be smaller just after raw history end. On the other hand, this implies that the model will diverge on long term. These settings are intended when prediction is used for at most 5 days after raw EOP end.

      Returns:
      fitter with default configuration for pole nutation parameters dx and dy
    • createDefaultNutationFitterLongTermPrediction

      public static SingleParameterFitter createDefaultNutationFitterLongTermPrediction()
      Create fitter with default parameters adapted for fitting nutation parameters dx and dy for long term prediction.

      The main difference between these settings and the settings for short prediction is the much larger \(\tau\). This means weight is spread throughout history, hence forcing the fitted prediction model to be remain very stable on the long term. On the other hand, this implies that the model will start with already a much larger error just after raw history end. These settings are intended when prediction is used for 5 days after raw EOP end or more.

      Returns:
      fitter with default configuration for pole nutation parameters dx and dy