Data Assimilation in the Detection of Vortices

被引：3

作者：

Barreiro, Andrea ^{[1
]}

Liu, Shanshan ^{[1
]}

Namachchivaya, N. Sri ^{[1
]}

Sauer, Peter W. ^{[1
]}

Sowers, Richard B. ^{[1
]}

机构：

[1] Univ Illinois, Dept Math, Urbana, IL 61801 USA

来源：

APPLICATIONS OF NONLINEAR DYNAMICS-MODEL AND DESIGN OF COMPLEX SYSTEMS | 2009年

基金：

美国国家科学基金会;

关键词：

PARTICLE FILTERS; TRACKING;

D O I：

10.1007/978-3-540-85632-0_5

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：47 / +

页数：2

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