Identifying optimal measurement subspace for ensemble Kalman filter

To reduce the computational load of the ensemble Kalman filter while maintaining its efficacy, an optimisation algorithm based on the generalised eigenvalue decomposition method is proposed for identifying the most informative measurement subspace. When the number of measurements is large, the proposed algorithm can be used to make an effective trade-off between computational complexity and estimation accuracy.