| 摘要: |
| 针对无线传感器网络中,节点受噪声影响导致测量精度下降的问题,提出一种基于滑动窗口内正态记分检验的同质感知数据融合方法.在节点内设置滑动窗口,存储一个周期内的测量值样本数据,并对样本数据进行双样本正态记分检验,从而建立关系矩阵,根据关系矩阵获得最大邻接子图,加权平均子图顶点得到融合估计值.该方法利用了正态记分检验良好的小样本检验特性,在一定程度上抑制了噪声对融合结果的影响.仿真结果表明了该方法的有效性. |
| 关键词: 无线传感器网络 滑动窗口 正态记分检验 数据融合 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金(1262020); 江西省科技支撑重点项目(2009BGA01000) |
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| Normal Score Test Data Fusion Method Based on Sliding Window for Wireless Sensor Networks |
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ZHU Ming-Ya1,2, SHU Jian1,3, LIU Lin-Lan1,2
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1.Internet of Things Technology Institute, Nanchang Hangkong University, Nanchang 330063, China;2.School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China;3.School of Software, Nanchang Hangkong University, Nanchang 330063, China
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| Abstract: |
| Due to the declining accuracy caused by noise in wireless sensor networks, a data fusion method called normal score test, based on sliding window, is proposed. With this method, a measured data sample in a cycle is taken as a sliding window, and a double sample normal score test is employed into samples. Furthermore, a relationship matrix is created to maximize the adjacent subgraph. An estimated fusion value is achieved in terms of weighting and averaging its vertices. To some extent, this method makes good use of the character of a normal score test and restrains the impact noise on fusion. Simulation results demonstrate the effectiveness of proposed method. |
| Key words: wireless sensor network sliding window normal score test data fusion |
