14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper FrB2.5

Gillijns, Steven (Katholieke Univ. of Leuven), Bernstein, Dennis S. (Univ. of Michigan), De Moor, Bart (Katholieke Univ. of Leuven)

The Reduced Rank Transform Square Root Filter for Data Assimilation

Scheduled for presentation during the Regular Session "Filtering and Smoothing" (FrB2), Friday, March 31, 2006, 16:50−17:10, Banquet Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on September 24, 2018

Keywords Filtering and Smoothing, Particle Filtering/Monte Carlo Methods


During the last decade, several suboptimal filtering schemes for data assimilation have been proposed. One of these algorithms, which has succesfully been used in several applications, is the Reduced Rank Square Root filter. In this paper, a numerically more efficient variation, the Reduced Rank Transform Square Root filter, is introduced. A theoretical comparison of both filters is given and their performance is analyzed by comparing assimilation results on a magnetohydrodynamic example which emulates a space storm interacting with the Earth's magnetosphere.