z-logo
open-access-imgOpen Access
Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks
Author(s) -
Jaechan Lim,
Uipil Chong
Publication year - 2015
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2015/837070
Subject(s) - rss , computer science , initialization , particle filter , tracking (education) , wireless sensor network , real time computing , power (physics) , algorithm , signal (programming language) , artificial intelligence , kalman filter , computer network , psychology , pedagogy , physics , operating system , quantum mechanics , programming language
We propose an algorithm for multitarget tracking by particle filtering in wireless sensor networks based on received signal strength (RSS) measurement where we also localize a newly appearing target whose location and reference power are unknown. Therefore, the number, the reference power, and the initial locations of targets are unknown in this problem. At the initial localization step, we apply approximate least squares (LS) method to roughly estimate the target location. After the initial location is estimated, we estimate the reference power. This is possible because we can use multiple number of measurements for estimating multiparameters. The proposed approach is particularly emphasized on the initialization step that completes the whole multitarget tracking system by particle filtering in a challenging scenario. The proposed approach is validated by computer simulations for its effectiveness.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom