Target classification in Wireless Sensor Network using Particle Swarm Optimization (PSO)

Author

Gharaibeh, Khaled M. ; Yaqot, Abdullah

Author_Institution

Telecommun. Eng. Dept., Yarmouk Univ., Irbid, Jordan

fYear

2012

fDate

7-9 Feb. 2012

Firstpage

1

Lastpage

5

Abstract

Target classification is one of the main requirements of target tracking processes in military Wireless Sensor Networks (WSN). In this paper, a new sub-optimal target classification approach based on Particle Swarm Optimization (PSO) is proposed. The PSO classification algorithm is shown to have better classification accuracy and processing speed as compared to the k-Nearest Neighbor (kNN) and Maximum Likelihood classification algorithms.

Keywords

military communication; particle swarm optimisation; pattern classification; target tracking; wireless sensor networks; PSO classification algorithm; k-nearest neighbor; maximum likelihood classification algorithm; military wireless sensor networks; particle swarm optimization; suboptimal target classification approach; target tracking process; Accuracy; Classification algorithms; Feature extraction; Particle swarm optimization; Support vector machine classification; Training; Wireless sensor networks; particle swarm optimization; target classification; target tracking; wireless sensor networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Sensors Applications Symposium (SAS), 2012 IEEE

Conference_Location

Brescia

Print_ISBN

978-1-4577-1724-6

Type

conf

DOI

10.1109/SAS.2012.6166290

Filename

6166290