TY - JOUR
T1 - Efficient particle filtering through residual nudging
AU - Luo, Xiaodong
AU - Hoteit, Ibrahim
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank Dr M. Bocquet, Dr C. Snyder and two anonymous reviewers for their constructive and inspiring comments and suggestions. We have also benefited from useful discussions with Dr Geir Naevdal and Dr Andreas Stordal at IRIS. Luo acknowledges partial financial support from the Research Council of Norway and industrial partners through the project 'Transient well flow modelling and modern estimation techniques for accurate production allocation'.
PY - 2013/5/15
Y1 - 2013/5/15
N2 - We introduce an auxiliary technique, called residual nudging, to the particle filter to enhance its performance in cases where it performs poorly. The main idea of residual nudging is to monitor and, if necessary, adjust the residual norm of a state estimate in the observation space so that it does not exceed a pre-specified threshold. We suggest a rule to choose the pre-specified threshold, and construct a state estimate accordingly to achieve this objective. Numerical experiments suggest that introducing residual nudging to a particle filter may (substantially) improve its performance, in terms of filter accuracy and/or stability against divergence, especially when the particle filter is implemented with a relatively small number of particles. © 2013 Royal Meteorological Society.
AB - We introduce an auxiliary technique, called residual nudging, to the particle filter to enhance its performance in cases where it performs poorly. The main idea of residual nudging is to monitor and, if necessary, adjust the residual norm of a state estimate in the observation space so that it does not exceed a pre-specified threshold. We suggest a rule to choose the pre-specified threshold, and construct a state estimate accordingly to achieve this objective. Numerical experiments suggest that introducing residual nudging to a particle filter may (substantially) improve its performance, in terms of filter accuracy and/or stability against divergence, especially when the particle filter is implemented with a relatively small number of particles. © 2013 Royal Meteorological Society.
UR - http://hdl.handle.net/10754/562765
UR - http://arxiv.org/abs/arXiv:1303.2698v1
UR - http://www.scopus.com/inward/record.url?scp=84896058472&partnerID=8YFLogxK
U2 - 10.1002/qj.2152
DO - 10.1002/qj.2152
M3 - Article
SN - 0035-9009
VL - 140
SP - 557
EP - 572
JO - Quarterly Journal of the Royal Meteorological Society
JF - Quarterly Journal of the Royal Meteorological Society
IS - 679
ER -