Title :
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
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;
Conference_Titel :
Sensors Applications Symposium (SAS), 2012 IEEE
Conference_Location :
Brescia
Print_ISBN :
978-1-4577-1724-6
DOI :
10.1109/SAS.2012.6166290
