传感技术学报2017，Vol.30Issue(10)：1525-1530,6.DOI:10.3969/j.issn.1004-1699.2017.10.012
一种基于数据预处理和卡尔曼滤波的 温室监测数据融合算法
A Data Fusion Algorithm on Data Preprocessing and Kalman Filter for Greenhouse Environment Monitor
摘要
Abstract
The greenhouse has the larger space,and the wireless nodes are vulnerable to the interference from the environment. The data collected by nodes are more volatile and many interference factors easily lead to packet loss. In order to enhance the reliability of wireless sensor neworks for the greenhouse monitoring,and improve the preci-sion of data fusion,a data fusion algorithm on data preprocessing and Kalman filter is proposed. Firstly,the data pre-processing method and Kalman filter is utilized to decrease the influence of abnormal data,then these data are sent to the cluster head and fused on the weighted data fusion algorithm with the state compensation strategy. The simula-tion is conducted on the greenhouse humidity, which shows that data preprocessing can significantly reduce data fluctuations, the amount of data transmission and the network energy consumption while improve the anti-interference ability of wirless networks. In addition,the weighted data fusion algorithm based on state compensation strategy can also significantly improve the fusion accuracy in the case of packet loss.关键词
无线传感器网络/数据融合/数据预处理/卡尔曼滤波/状态补偿/湿度Key words
wireless sensor network/data fusion/data preprocessing/Kalman filter/state compensation/humidity分类
信息技术与安全科学引用本文复制引用
王振,白星振,马梦白,张致境,高正中..一种基于数据预处理和卡尔曼滤波的 温室监测数据融合算法[J].传感技术学报,2017,30(10):1525-1530,6.基金项目
中国博士后基金项目(2014M551934) （2014M551934）
山东省中青年科学家奖励基金项目(BS2013DX012) （BS2013DX012）
山东省博士后基金项目(201303068) （201303068）
