• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2010, Vol. 32 ›› Issue (11): 33-35.

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基于统计假设检验的传感器网络目标探测机制

崔逊学1,邢立军1,方震2   

  1. (1.解放军炮兵学院,安徽 合肥 230031;2.中国科学院电子学研究所传感技术国家重点实验室,北京 100080)
  • 收稿日期:2010-07-13 修回日期:2010-09-12 出版日期:2010-11-25 发布日期:2010-11-25
  • 作者简介:崔逊学(1969),男,安徽桐城人,博士,副教授,CCF会员(E200008840M),研究方向为传感器网络、智能优化和目标定位;邢立军,硕士,研究方向为无线传感器网络和目标探测;方震,博士,副研究员,研究方向为物联网和无线传感器网络。
  • 基金资助:
    国家自然科学基金资助项目(60773129)

A Target Detection Mechanism in Sensor Networks Based on Statistical Hypothesis Testing

CUI Xun xue1,XING Lijun1,FANG Zhen2   

  1. (1.Artillery Academy of PLA,Hefei 230031; 2.The State Key Laboratory of Transducer Technology,Institute of Electronics,Chinese Academy of Sciences,Beijing 100080,China)
  • Received:2010-07-13 Revised:2010-09-12 Online:2010-11-25 Published:2010-11-25

摘要: 多传感器组网对目标探测是当前军事领域的研究热点,也是传感器网络的基本功能。但是,现有的基于目标输出信号阈值机制难以精确描述目标发现事件。根据数理统计理论将目标探测问题建模为统计推断过程,本文提出一种基于统计假设检验的传感器网络目标探测机制,通过样本训练确定检验参数,采用数据融合方法优化探测结果。实验显示,该方法能有效解决探测过程的噪声干扰问题,提高目标捕捉的正确率。

关键词: 传感器网络, 目标探测, 数据融合, 统计假设检验

Abstract: It is a hot research topic in the current military field that target detection is executed with many sensors in a networking manner. Target detection is also the fundamental function of a sensor network. However it is difficult for the current mechanism to describe the target discovery event which is based on an output signal threshold of the target. According to the mathematical statistics theory, the problem of target detection is modeled as a statistical inference process in the paper. A target detection mechanism based on the hypothesis testing method is proposed. In this mechanism the testing parameters can be determined by a sample training process, and moreover a data fusion method is adopted for the detection result optimization. The experimental results show that this mechanism can avoid the noise interference in the detection process, and improve the exactness performance of target catch in sensor networks.

Key words: sensor network, target detection, data fusion, statistical hypothesis testing