Multi-sensor Distributed Information Fusion Unscented Particle Filter

被引：0

作者：

Mao Lin ^{[1
,2
]}

Liu Sheng ^{[1
]}

机构：

[1] Harbin Engn Univ, Dept Automat, Harbin 150001, Peoples R China

[2] Heilongjiang Univ, Dept Elect Engn, Harbin 150080, Peoples R China

来源：

PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE | 2010年

关键词：

Information Fusion; Unscented Particle Filter; State estimation;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, an unscented particles filter based distributed information fusion is proposed for state estimation problem of nonlinear and non-Gaussian systems. It uses unscented Kalman filter algorithm to update particle; then calculates local state estimated values by particle filter. The systemfusion estimation is obtained by applying the fusion rule weighted by scales. The simulation results show that compared with single sensor, the proposed algorithm improves the accuracy of filter.

引用

页码：296 / 299

页数：4