摘要
无线传感器网络(wireless sensor networks)作为一种重要的信息获取和处理技术,可以在广泛的领域内实现目标监测、信息采集和目标追踪等任务,节点定位是无线传感器网络的重要支撑技术之一。而传统的定位算法具有定位误差大或定位率低的缺点。在对质心定位算法和DV-Hop定位算法的原理进行深入分析的基础上,提出了一种质心和DV-Hop混合定位算法MCDA,MCDA从3个方面提高了定位性能:首先通过设置TTL(time to live)值来限制锚节点广播数据包的范围,减少DV-Hop算法的通信开销;其次提高邻居锚节点的比例;最后通过改进质心定位算法减小定位误差。仿真结果表明,当锚节点数为5时,与DV-Hop定位算法相比,MCDA的平均定位误差降低了53.7%。当锚点数增加到10和20时,与质心定位算法相比,MCDA的平均定位率提高了28.5%和14.2%。
Wireless sensor networks is an important information acquisition and processing technology.It can perform tasks such as target monitoring,information collection and target tracking in a wide range of fields.Node location problem is the basis of many applications and the supporting technology of WSN.Traditional localization algorithms contain defects of large localization error or low localization ratio.Based on the in-depth analysis of the principle of the centroid localization algorithm and the DV-Hop localization algorithm,this paper proposed a localization algorithm that mixed the centroid and DV-Hop algorithms MCDA,which improved the localization performance from three aspects.Firstly,by setting the TTL(time to live)value,the range of the anchor node broadcast packet is limited to reduce the communication overhead of DV-Hop.Secondly,the proportion of neighbor anchor nodes was increased,so that when the anchor nodes of the centroid localization algorithm are low,the problem of low localization ratio is improved.Finally,the centroid localization algorithm is improved to reduce the localization error.The simulation results show that when the number of anchor nodes is 5,the average localization error of MCDA is reduced by 53.7%compared with that of the DV-Hop algorithm.When the number of anchor nodes increases to 10 and 20,the average localization ratio of MCDA is improved by 28.5%and 14.2%compared with that of the centroid localization algorithm.
作者
张悦
梁建国
张浩
花嵘
冯鲁彬
ZHANG Yue;LIANG Jian-guo;ZHANG Hao;HUA Rong;FENG Lu-bin(School of Computer Science and Engineering,Shandong University of Science and Technology,Qingdao 266590,China)
出处
《仪表技术与传感器》
CSCD
北大核心
2021年第4期122-126,共5页
Instrument Technique and Sensor
基金
国家重点研发计划子课题(2017YFB0202002)
山东省重点研发项目(2019GGX101066)。