The ensemble Kalman filter and its relations to other nonlinear filters

Michael Roth, Carsten Fritsche, Gustaf Hendeby, Fredrik Gustafison
2015 2015 23rd European Signal Processing Conference (EUSIPCO)  
The Ensemble Kalman filter (EnKF) is a standard algorithm in oceanography and meteorology, where it has got thousands of citations. It is in these communities appreciated since it scales much better with state dimension n than the standard Kalman filter (KF). In short, the EnKF propagates ensembles with N state realizations instead of mean values and covariance matrices and thereby avoids the computational and storage burden of working on n × n matrices. Perhaps surprising, very little
more » ... has been devoted to the EnKF in the signal processing community. In an attempt to change this, we present the EnKF in a Kalman filtering context. Furthermore, its application to nonlinear problems is compared to sigma point Kalman filters and the particle filter, so as to reveal new insights and improvements for high-dimensional filtering algorithms in general. A simulation example shows the EnKF performance in a space debris tracking application.
doi:10.1109/eusipco.2015.7362581 dblp:conf/eusipco/RothFHG15 fatcat:zmjsusuolrby7dvdl52eja6uoi