计算机应用 ›› 2012, Vol. 32 ›› Issue (11): 3112-3124.DOI: 10.3724/SP.J.1087.2012.03112

• 网络与通信 • 上一篇    下一篇

基于卡尔曼滤波和数据关联的无线网络状态融合方法

段谟意   

  1. 南京铁道职业技术学院 软件学院,南京 210031
  • 收稿日期:2012-06-25 修回日期:2012-07-29 发布日期:2012-11-12 出版日期:2012-11-01
  • 通讯作者: 段谟意
  • 作者简介:段谟意(1964-), 男, 江西都昌人, 副教授, 主要研究方向:计算机网络。
  • 基金资助:
    全国教育科学”十二五”规划教育部规划课题(FJB110092)

Status fusion method for wireless network based on Kalman filtering and data associated

DUAN Mo-yi   

  1. School of Software Engineering, Nanjing railway Vocational and Technical College, Nanjing Jiangsu 210031,China
  • Received:2012-06-25 Revised:2012-07-29 Online:2012-11-12 Published:2012-11-01
  • Contact: DUAN Mo-yi

摘要: 为了解决无线网络传输过程中受到干扰信号影响所产生的性能问题,提出一种新的信号状态融合方法(SFWD)。该方法首先基于小波变换降低信号的长相关特性,并且利用卡尔曼滤波和数据关联建立融合算法。通过仿真实验对比研究了信号状态与干扰因素之间的关系,结果表明该方法具有一定的适应性,其融合结果与原始信号之间的标准差为7.13。

关键词: 干扰信号, 融合, 长相关, 小波, 数据关联

Abstract: In order to mitigate the performance by interference signal in wireless network transmission, a new signal status fusion method SFWD (Signal Fusion based on Wavelet transform and Data association) was proposed. In this method, the longrange dependence of signal was reduced by wavelet transform at first, and the fusion algorithm was established with Kalman filter and date association. Then, a simulation was conducted to research the relationship between the signal status and influencing factors. The result shows that it is of adaptability with wireless network signal, and the standard deviation between the fusion signal data and original signal is 7.13.

Key words: interference signal, fusion, longrange dependence, wavelet, data association

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