EconPapers    
Economics at your fingertips  
 

A Grid-Based Linear Least Squares Self-Localization Algorithm in Wireless Sensor Network

Wei Wang, Haoshan Shi, Pengyu Huang, Dingyi Fang, Xiaojiang Chen, Yun Xiao and Fuping Wu

International Journal of Distributed Sensor Networks, 2015, vol. 11, issue 8, 317603

Abstract: Self-localization is one of the key technologies in the wireless sensor networks (WSN). Some traditional self-localization algorithms can provide a reasonable positioning accuracy only in a uniform and dense network, while for a nonuniform network the performance is not acceptable. In this paper, we presented a novel grid-based linear least squares (LLS) self-localization algorithm. The proposed algorithm uses the grid method to screen the anchors based on the distribution characteristic of a nonuniform network. Furthermore, by taking into consideration the quasi-uniform distribution of anchors in the area, we select suitable anchors to assist the localization. Simulation results demonstrate that the proposed algorithm can greatly enhance the localization accuracy of the anonymous nodes and impose less computation burden compared to traditional Trilateration and Multilateration.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2015/317603 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:11:y:2015:i:8:p:317603

DOI: 10.1155/2015/317603

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().

 
Page updated 2025-04-12
Handle: RePEc:sae:intdis:v:11:y:2015:i:8:p:317603