Navigation system of a class of underwater vehicle based on adaptive unscented Kalman fiter algorithm

被引：0

作者：

刘开周 ^{[1
]}

李静 ^{[2
]}

郭威 ^{[1
]}

祝普强 ^{[1
]}

王晓辉 ^{[1
]}

机构：

[1] State Key Laboratory of Robotics (Shenyang Institute of Automation,Chinese Academy of Sciences)

[2] Graduate University of Chinese Academy of Sciences

来源：

Journal of Central South University | 2014年 / 21卷 / 02期

基金：

中国国家自然科学基金;

关键词：

human occupied vehicle; navigation; extended Kalman filter; unscented Kalman filter; adaptive unscented Kalman filter;

D O I：

暂无

中图分类号：

U666.1 [导航设备]; U674.941 [潜水船];

学科分类号：

081105 ; 082401 ;

摘要：

Inherent flaws in the extended Kalman filter(EKF) algorithm were pointed out and unscented Kalman filter(UKF) was put forward as an alternative.Furthermore,a novel adaptive unscented Kalman filter(AUKF) based on innovation was developed.The three data-fusing approaches were analyzed and evaluated in a mathematically rigorous way.Field experiments conducted in lake further demonstrate that AUKF reduces the position error approximately by 65% compared with EKF and by 35% UKF and improves the robust performance.

引用

页码：550 / 557

页数：8

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