多传感器时间控制系统的数据融合新算法

熊彦铭; 李世玲; 李军; 杨战平

doi:10.15892/j.cnki.djzdxb.2012.01.010

2012 , Vol. 32 >Issue 1: 171 - 174

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2012.01.010

摘要

针对由多个传感器组成的时间控制系统,为满足其较高的实时性和鲁棒性要求,提出了一种新的加权融合算法。该方法不需要传感器测量值的先验信息,根据实测数据之间的相互关系来确定门限和权值分配策略,避免了设定经验门限带来的主观因素。仿真试验和工程实际应用均表明:该算法鲁棒性强,融合精度高,且计算量小,满足系统的高实时性要求,具有一定的理论意义和较高的工程实用价值。

关键词： 多传感器时间控制系统; 数据融合; 权值分配; 实时性; 鲁棒性

本文引用格式

熊彦铭 , 李世玲 , 李军 , 杨战平 . 多传感器时间控制系统的数据融合新算法[J]. 弹箭与制导学报, 2012 , 32(1) : 171 -174 . DOI: 10.15892/j.cnki.djzdxb.2012.01.010

Abstract

A novel adaptive weighted fusion method was proposed for multi-sensor delay-control system. No prior information of distribution was needed; the threshold value and the weight assignment were decided adaptively according to the relationship among the measured data, by which the subjective factors in setting experiential threshold value were avoided. Numerical examples show that the proposed method takes on strong robustness and good real-time performance, and it has theoretical and practical significance.

Key words： multi-sensor delay-control system; data fusion; weight assignment; real-time performance; robustness

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参考文献

[1]	Qi HR, Iyengar SS, Chakrabarty K. Distributed sensor network: A review of recent research[J]. Journal of the Franklin Institute, 2001, 338 (6): 655- 668.
[2]	John MR. Fusion of multi-sensor data[J]. Journal of Robotics Research, 1998, 7 (6): 78- 96.
[3]	吴小俊, 曹奇英, 陈保香. 基于Bayes 估计的多传感器数据融合方法研究[J]. 系统工程理论与实践, 2000 (7): 46- 49.
[4]	Odeberg H. Distance measure for sensor opinions[J]. Measurement science and technology, 1993, 4 (8): 808- 815.
[5]	Wang JH, Gao Y. Multi-sensor data fusion for land vehicle attitude estimation using fuzzy expert system[J]. Data Science Journal, 2005 (4): 127- 139.
[6]	刘建书, 李人厚, 常宏,等. 基于相关性函数和最小二乘的多传感器数据融合[J]. 控制与决策, 2006 (6): 715- 718.
[7]	胡振涛, 刘先省. 基于相对距离的一种多传感器数据融合方法[J]. 系统工程与电子技术, 2006 (2): 42- 44.
[8]	韩峰, 杨万海, 袁晓光. 基于相关性函数和模糊贴近度的多传感器数据融合[J]. 弹箭与制导学报, 2009, 29 (4): 227- 229.
[9]	Chung ACS, Shen HC. Integrating dependent sensory data[C]// Proceeding of 1998 IEEE Inter. Conf. on Robotics and Automation, 1998: 3546- 3551.
[10]	Xu LJ, LiXM, Dong F. Optimum estimation of the mean flow velocity for the multi-electrode inductance flowmeter[J]. Means Science Technology, 2001, 12 (6): 1139- 1146.
[11]	王华, 邓军, 王连华,等. 改进的一致性数据融合算法及其应用[J]. 中国矿业大学学报, 2009, 38 (4): 590- 594.
[12]	陈忠德, 蒋静坪. 一致性多传感器数据融合方法的改进[J]. 传感器技术, 1995 (5): 52- 55.
[13]	凌林本, 李滋刚, 陈超英,等. 多传感器数据融合时权的最优分配原则[J]. 中国惯性技术学报, 2000, 8 (2): 36- 39.

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