计算机科学 ›› 2012, Vol. 39 ›› Issue (Z6): 24-27.

• • 上一篇    下一篇

支持无线传感器网络多目标跟踪的聚类数据关联算法研究

朱晓钢,杨兵,许华杰   

  1. (湖北大学数学与计算机学院 武汉430062);(湖北大学教育学院 武汉430062);(上海第二工业大学计算机与信息学院 上海201209)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Clustering Data Association Algorithm to Support Multi-target Tracl}ing in WSN

  • Online:2018-11-16 Published:2018-11-16

摘要: 多源数据关联问题是无线传感器网络中多传感器数据融合的关键技术之一。联合概率数据关联算法是一种 跟踪多目标的数据关联算法,它不需要任何关于目标和杂波的先验信息,但与其他有关数据关联算法相比,计算机开 销大。基于聚类算法的联合概率数据关联算法在联合概率数据关联算法的基础上,运用模式识别中的聚类思想对传 感器所接收到的量测数据进行聚类,减少有效量测的数目,从而简化了有效矩阵,减少了原有算法的计算量。

关键词: 传感器网络,多目标跟踪,联合概率数据关联,聚类

Abstract: Multi-source data association is one of the key technologies of multi-sensor data fusion in wireless sensor net- work. The joint probability data association algorithm is a data association algorithm of Multi-target tracking, and it doesn't need any priori information about targets and clutters, but its computer expense is very large compared with the other related data association algorithms. The joint probability data association algorithm based on clustering algorithm applys the cogitation of clustering in pattern recognition to deal with the measurement data received from sensors. I}his method reduces the number of measurement data, and simplifies the effective matrix, thus reduces the computation of o- riginal algorithm.

Key words: Wireless sensor network, Multi-target tracking, Joint probability data association, Cluster

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!