TY - CHAP
T1 - Data assimilation in the detection of vortices
AU - Barreiro, Andrea
AU - Liu, Shanshan
AU - Sri Namachchivaya, N.
AU - Sauer, Peter W.
AU - Sowers, Richard B.
PY - 2009
Y1 - 2009
N2 - We develop new algorithms for target detection in multi-sensor environments. These methods are applied to study point vortex motion based on Lagrangian tracer information. First we solve analytically the nonlinear filtering problem for the special case of equal strength vortices. Recently developed methods, the particle filters that are based on importance sampling Monte Carlo simulations, are used for the detection of vortices in the the general case. Unlike the well-known extended Kalman filter, it is applicable to highly nonlinear systems with non-Gaussian uncertainties.
AB - We develop new algorithms for target detection in multi-sensor environments. These methods are applied to study point vortex motion based on Lagrangian tracer information. First we solve analytically the nonlinear filtering problem for the special case of equal strength vortices. Recently developed methods, the particle filters that are based on importance sampling Monte Carlo simulations, are used for the detection of vortices in the the general case. Unlike the well-known extended Kalman filter, it is applicable to highly nonlinear systems with non-Gaussian uncertainties.
UR - http://www.scopus.com/inward/record.url?scp=62849108695&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=62849108695&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85632-0_5
DO - 10.1007/978-3-540-85632-0_5
M3 - Chapter
AN - SCOPUS:62849108695
SN - 9783540856313
T3 - Understanding Complex Systems
SP - 47
EP - 59
BT - Applications of Nonlinear Dynamics
ER -