WSNs target tracking algorithm based on probability threshold communication perception

SHEN Cai-liang; DU Huan-qiang

doi:10.13873/J.1000-9787(2015)04-0111-04

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WSNs target tracking algorithm based on probability threshold communication perception

更新时间：2025-09-11

- WSNs target tracking algorithm based on probability threshold communication perception
- Vol. 34, Issue 4, Pages: 111-114(2015)
- 作者机构：
  
  1. 浙江大学计算机科学与技术学院
  2. 浙江工业职业技术学院设计与艺术分院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)04-0111-04
  CLC： TN929.5;TP212.9
- Published：2015
- 稿件说明：
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[1]沈才樑,杜焕强.基于概率阈值通信感知的WSNs目标跟踪算法[J].传感器与微系统,2015,34(04):111-114.

SHEN Cai-liang, DU Huan-qiang. WSNs target tracking algorithm based on probability threshold communication perception[J]. 2015, 34(4): 111-114.
[1]沈才樑,杜焕强.基于概率阈值通信感知的WSNs目标跟踪算法[J].传感器与微系统,2015,34(04):111-114. DOI： 10.13873/J.1000-9787(2015)04-0111-04.

SHEN Cai-liang, DU Huan-qiang. WSNs target tracking algorithm based on probability threshold communication perception[J]. 2015, 34(4): 111-114. DOI： 10.13873/J.1000-9787(2015)04-0111-04.

摘要

针对移动Sink节点目标跟踪定位时间长

能耗大等问题

提出基于概率阈值通信感知的WSNs目标跟踪算法。采用离散数据传输方式

并定义目标信息传输概率阈值来确定是否将节点当前位置信息由传感器节点传输到Sink节点。若当前位置信息不传输到Sink节点中

则使用最近一次通报的目标位置信息进行目标定位。然后开启目标周围相关传感器节点来有效降低算法数据传输量

并保持足够的定位精度。仿真结果显示:该方法比预测跟踪算法降低数据传输量87%左右

比动态目标跟踪算法降低跟踪时间33.7%左右。

Abstract

Aiming at problem of long time of target tracking and localization and high energy consumption of mobile sink node

WSNs target tracking algorithm based on probability threshold communication perception is proposed. Adopt discrete data transmission mode

and define probability threshold of target information transmission to determine whether transmit current location information of node from sensor nodes to sink node or not. If current position information is not transmitted to the Sink node

the recent notification of target positioning information is used. Then the related wireless sensor nodes around the target are opened

through this way the amount of data transmission is reduced

and sufficient positioning precision is maintained. The simulation results show that

the method can reduce data transmission quantity about 87 %

compared with the forecast tracking algorithm

and reduce the tracking time about 33. 7 %

compared with the dynamic target tracking algorithm.

关键词

Keywords

references

单节点的无线传感器网络数据传输优化策略 [J]. 吴金舟,王明文,胡剑锋,杨国强. 传感器与微系统 . 2014(12)

基于能量和距离的分区域选择簇首WSNs路由算法 [J]. 刘永超,张月霞,缪旻. 传感器与微系统 . 2015(01)

Uncertainty-based information extraction in wireless sensor networks for control applications [J] . Bart?omiej P?aczek,Marcin Berna?. Ad Hoc Networks . 2013

Mobile object tracking in wireless sensor networks [J] . Hua-Wen Tsai,Chih-Ping Chu,Tzung-Shi Chen. Computer Communications . 2007 (8)

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