摘要
无线传感器网络是一种新兴的、全新的技术,它常常应用于工业领域以及恶劣的环境中.在标准ZigBee协议中没有设计相关的数据融合规范,使其只能用在低数据冗余的应用场合.大规模网络中的数据冗余度大,并且网络中的数据冗余会引起节点频繁地争抢信道,网络时延增加甚至出现网络瘫痪;因此针对同类多传感器测量数据中含有的噪声和传输中包含大量冗余信息,通过多次实验对几种算法进行仿真比较,文中提出了一种基于递推估计的数据融合和自适应加权时空融合算法.该算法利用空间位置中多传感器的方差变化,通过调整参与融合的各传感器的加权系数,使融合系统均方误差始终最小.
Wireless sensor network is a new technology which can be applied to industry and ill-being. The related data fusion standard is not designed in the standard ZigBee agreement and therefore it can only be applied to low data redundancy. Large-scale network data redundancy degree and the data redundancy in the network nodes often cause competition for the channel, the network delay even leads to network paralysis. Moreover, the same kinds of multi-sensor measurement contains noise and a lot of redundant information,thus an algorithm was put forward based on the validity and their difference of the precision in data fusion after many tests and simulation. It could make the mean square error minimal by adjusting the fused sensor＇s weight in time according to the change in sensor＇s variance.
出处
《应用科技》
CAS
2011年第11期30-33,共4页
Applied Science and Technology
