Implicit sampling for particle filters

被引：104

作者：

Chorin, Alexandre J. ^{[1
]}

Tu, Xuemin

机构：

[1] Univ Calif Berkeley, Dept Math, Berkeley, CA 94720 USA

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 2009年 / 106卷 / 41期

基金：

美国国家科学基金会;

关键词：

pseudo-Gaussian; Jacobian; chainless sampling; MONTE-CARLO;

D O I：

10.1073/pnas.0909196106

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We present a particle-based nonlinear filtering scheme, related to recent work on chainless Monte Carlo, designed to focus particle paths sharply so that fewer particles are required. The main features of the scheme are a representation of each new probability density function by means of a set of functions of Gaussian variables (a distinct function for each particle and step) and a resampling based on normalization factors and Jacobians. The construction is demonstrated on a standard, ill-conditioned test problem.

引用

页码：17249 / 17254

页数：6

共 21 条

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