| 引用本文: | 刘秀罗,黄柯棣.数据融合技术在CGF建模中的应用.[J].国防科技大学学报,2001,23(3):103-106.[点击复制] |
| LIU Xiuluo,HUANG Kedi.Application of Data Fusion Technology in CGF Modeling[J].Journal of National University of Defense Technology,2001,23(3):103-106[点击复制] |
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| 数据融合技术在CGF建模中的应用 |
| 刘秀罗, 黄柯棣 |
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(国防科技大学 机电工程与自动化学院,湖南 长沙 410073)
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| 摘要: |
| 提出了将数据融合技术应用到计算机生成兵力（CGF）建模中的思路和方法。在分析数据融合技术的基础上，深入讨论了卡尔曼滤波和最小二乘相结合的滤波方法以及一种改进的离散Hopfield神经网络，并结合一实际系统，建立了模型，给出了仿真结果。结果表明，数据融合技术和CGF建模相结合具有一定的应用前景和研究价值。 |
| 关键词: CGF 数据融合 卡尔曼滤波 Hopfield神经网络 |
| DOI： |
| 投稿日期：2000-10-08 |
| 基金项目:国家部委基金项目(99J16.5.1.KG0139) |
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| Application of Data Fusion Technology in CGF Modeling |
| LIU Xiuluo, HUANG Kedi |
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(College of Mechatronics Engineering and Automation, National Univ. of Defense Technology, Changsha 410073, China)
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| Abstract: |
| A method of applying data fusion technology to computer generated forces modeling is presented. It first analyzes data fusion technology, then discusses in detail the filtering method of combining Kalman filtering and least square, and an improved Hopfield neural network as well. With applying these models to a practical system, the simulation result is given. It holds a great promise of combining data fusion technology with CGF modeling. |
| Keywords: computer generated forces data fusion kalman filtering Hopfield neural network |
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