Multi-target Particle Filter Tracking Algorithm Based on Wireless Sensor Networks

• Main Authors: Liu Hong-Xia, Zhang Feng, Zhang Yong-Heng, Wu Min-Ning
• Format: Article
• Language: English
• Published: IFSA Publishing, S.L. 2014-05-01
• Series: Sensors & Transducers
• Subjects: Particle filter; Wireless wireless sensor; Target tracking; Automatic control; Localization algorithm.
• Online Access: http://www.sensorsportal.com/HTML/DIGEST/may_2014/Vol_170/P_2046.pdf
• ISSN: 2306-8515; 1726-5479

In order to improve the multi-target tracking efficiency for wireless sensor networks and solve the problem of data transmission, analyzed existing particle filter tracking algorithm, ensure that one of the core technology for wireless sensor network performance. In this paper, from the basic theory of target tracking, in-depth analysis on the basis of the principle of particle filter, based on dynamic clustering, proposed the multi-target Kalman particle filter (MEPF) algorithm, through the expansion of Calman filter (EKF) to generate the proposal distribution, a reduction in the required number of particles to improve the particle filter accuracy at the same time, reduce the computational complexity of target tracking algorithm, thus reducing the energy consumption. Application results show that the MEPF in the proposed algorithm can achieve better tracking of target tracking and forecasting, in a small number of particles still has good tracking accuracy.