[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(2):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(2):44-47.
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LI Ye,CHANG Wen-tian,WAN Lei,et al.Research on underwater vehicle adaptive Kalman filter[J].CAAI Transactions on Intelligent Systems,2006,1(2):44-47.
水下机器人自适应卡尔曼滤波技术研究
《智能系统学报》[ISSN1673-4785/CN23-1538/TP] 卷:
第1卷
期数:
2006年2期
页码:
44-47
栏目:
学术论文—智能系统
出版日期:
2006-10-25
- Title:
- Research on underwater vehicle adaptive Kalman filter
- 文章编号:
- 1673-4785(2006)02-0044-04
- 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 timevaried 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:
-
［1］刘建成, 徐玉如. 水下机器人神经网络滤波技术的研究［J］. 海洋工程, 2002, 20( 3): 34－38.
LIU Jiancheng, XU Yuru. A filtering method with neural network for underwate r vehicle ［J］. Ocean Engineering, 2002, 20(3): 34－38.
［2］ WANG Y F,HAN X L，HU H Z. Study on federated archi tecture for GPS/INS/TRN integrated navigation system ［J］. Journal of Systems E ngineering and E lectronics,2000,11(1):75－80.
［3］ SASIADEK J Z, WANG Q，ZEREMBA M B. Fuzzy adoptive Kalman filtering f or INS/GPS data fusion ［A］. In：Proc 15th IEEE International Symposium on Int elligent Control［C］. Patras, Greece, 2000.
［4］ 朱 海, 莫 军. 水下导航信息融合［M］. 北京：国防工业出版社，2002.
［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.
［6］ 马 艳.数据融合技术在多传感器组合导航中的应用［D］. 南京: 南京航空航天大学, 2000.
MA Yan. Information amalgamation in multisensors combined navigation ［D］. Na njing: Nanjing University of Aeronautics and Astronautics, 2000
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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