[1]李 晔,常文田,万 磊,等.水下机器人自适应卡尔曼滤波技术研究[J].智能系统学报,2006,1(02):44-47.
 LI Ye,CHANG Wen-tian,WAN Lei,et al.Research on underwater vehicle adaptive Kalman filter[J].CAAI Transactions on Intelligent Systems,2006,1(02):44-47.
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水下机器人自适应卡尔曼滤波技术研究(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第1卷
期数:
2006年02期
页码:
44-47
栏目:
出版日期:
2006-10-25

文章信息/Info

Title:
Research on underwater vehicle adaptive Kalman filter
文章编号:
1673-4785(2006)02-0044-04
作者:
李 晔常文田万 磊孙玉山
哈尔滨工程大学船舶工程学院,黑龙江哈尔滨150001
Author(s):
LI YeCHANG Wen-tian WAN Lei SUN Yu-shan
College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
关键词:
水下机器人卡尔曼滤波自适应
Keywords:
underwater vehicle Kalman filter adaptive
分类号:
TP24
文献标志码:
A
摘要:
水下机器人的位置和速度传感器受环境影响较大,数据滤波问题是运动控制的核心问题之一.给出了离散型卡尔曼滤波的基本方程,描述了卡尔曼滤波所具有的两个计算回路:增益计算回路和滤波计算回路.建立了水下机器人状态方程和量测方程,并在此基础上采用了自适应卡尔曼滤波方法对水下机器人的传感器数据进行了滤波分析.引入了渐消记忆指数加权方法.对时变噪声统计中,强调了新近数据的作用.避免了系统误差和量测误差统计特性的不准确对系统滤波效果的影响.滤波效果分析表明此方法能达到很好的滤波效果.
Abstract:
AUV position and velocity sensors are affected by environment. Data fi ltering is one of important problems of AUV motion control. Discrete basic Kalma n filter equation is given. Two loops of Kalman filter: plus loop and filter loo p are described. AUV state equation and measuring equation are founded. Data fro m AUV sensors are disposed by adaptive Kalman filter with fading exponent. Fadin g memory exponent is introduced. New data are emphasized for timevaried data. T his method avoids inaccuracy by system error and measuring error. Filter effect analysis proves that the method is effective. 

参考文献/References:

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 LIU Jiancheng, XU Yuru. A filtering method with neural network for underwate r vehicle [J]. Ocean Engineering, 2002, 20(3): 34-38.
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[5] 秦永元, 张洪钺,汪淑华. 卡尔曼滤波与组合导航原理[M]. 西安:西北工业大学出版社,1998.
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备注/Memo

备注/Memo:
收稿日期:2006-01-01.
基金项目:国家863基金资助项目(2002AA420090).
作者简介:
李 晔,男,1978年生,博士研究生,主要研究方向为水下机器人规划与运动控制,人工智能.
E-mail:liyelijing@yahoo.com.cn. 
万 磊,男,1964年生,研究员,船舶与海洋结构物设计制造专业硕士研究生导师,主要研究方向为水下机器人控制系统设计与集成,水下导航.发表学术论文多篇.
更新日期/Last Update: 2009-04-27