LOCALIZATION IN WSN USING MAXIMUM LIKELIHOOD ESTIMATION WITH NEGATIVE CONSTRAINTS BASED ON PARTICLE SWARM OPTIMIZATION

被引：0

作者：

Ding Haiqiang ^{[1
]}

Chen Hejun ^{[1
]}

Zhuang Hualiang ^{[1
]}

He Xiongxiong ^{[1
]}

机构：

[1] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou, Zhejiang, Peoples R China

来源：

2014 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP) | 2014年

关键词：

localization; maximum likelihood estimation; positive constrains; negative constrains; Particle Swarm Optimization;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we propose a maximum likelihood estimation approach with negative constraints to realize the localization of the unknown nodes in wireless sensor network. The main work can be divided into three parts: firstly, we measure the distance based on received signal strength from the nodes. Secondly, a series of positive and negative constrains are combined to build the modeling using the maximum likelihood estimation Finally, particle swarm optimization is employed to find the optimal position. The simulation results show that the proposed approach outperforms some existing localization algorithm without negative constrains.

引用

页码：2185 / 2189

页数：5

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