基于时延传感器网络的预测融合算法研究  

Study of predict fusion method based on multisensor time-delay network

作　　者：朱凤春[1] 戴炬[1] 赵协广[1] 

机构地区：[1]山东科技大学信息与电气工程学院

出　　处：《计算机应用研究》2007年第10期302-304,共3页Application Research of Computers

基　　金：国家"863"计划资助项目(2005AA420062)

摘　　要：现有的基于网络时延的融合算法大都直接套用传统的同步数据融合方法,因此会产生信息等待、资源闲置以及差的实时性能等问题。针对上述问题,在现有工作基础上,结合预测估计以及顺序加权融合技术,设计出了一种新的能适应网络时延的多传感器预测加权融合算法。该算法不仅能很好地解决现有基于时延的数据融合算法存在的诸多弊端,同时获得了良好的实时预测功能,并给出了新的基于网络时延的预测加权融合算法的推导过程,通过计算机仿真算例和理论分析来显示新算法的实用性和优越性。The existing fusion methods based on network-delay often were used the traditional synchronous fusion algorithms directly, so some questions would be produced, such as information delay, resource free, and bad real-time performance etc. Aiming at above questions this paper combined the predict estimate with the technology of sequential weighted fusion at the basis of the existing research, accordingly a new multisensor predict weighted fusion method which could adapt to network-delay was proposed. The new method can not only avoid the disadvantages existing in the current data fusion method founded on network delay and it gains the better real-time predict function. It presented the process to deduce the sequential predict weighted method based on network-delay. Moreover, the computer simulation and theoretical analysis were used to show the practicability and advantage of the proposed fusion method.

关 键 词：网络时延 多传感器系统 线性无偏估计 最优 预测加权融合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TP393[自动化与计算机技术—计算机科学与技术]