Ensemble Square Root Updater #669
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Codecov Report
@@ Coverage Diff @@
## main #669 +/- ##
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+ Coverage 94.55% 94.56% +0.01%
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Files 168 168
Lines 8441 8459 +18
Branches 1633 1634 +1
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+ Hits 7981 7999 +18
Misses 343 343
Partials 117 117
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| @@ -118,19 +114,18 @@ def predict_measurement(self, predicted_state, measurement_model=None, | |||
| measurement_model : :class:`~.MeasurementModel` | |||
| The measurement model. If omitted, the model in the updater object | |||
| is used | |||
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It should be noted that this pull request now includes the changes outlined in the discussion of Issue #668. This include changes to numerous |
Here is my implementation of the Ensemble Square Root filter Updater which I presented at last year's Fusion Conference.
A full writeup of the algorithm itself, as well as design philosophy can be found in my paper titled "Implementation of Ensemble Kalman Filters in Stone Soup". The contribution here (in this particular pull request) is specifically a new updater. The predictor of the EnKF and EnSRF are shared, but the EnSRF assimilates measurements without adding noise which typically results in lower sampling error and thus higher accuracy.
One other thing to note. Is that this pull request also fixes issue #668 which caused both the
EnsemblePredictorand thepredict_measurementmethod in the EnKF (the latter of which is inherited by the EnSRF).