By Topic

Dynamic searching particle filtering scheme for indoor localization in wireless sensor network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Yubin Zhao ; Inst. of Comput. Sci., Freie Univ. Berlin, Berlin, Germany ; Yuan Yang ; Kyas, M.

In this paper, we propose a robust and efficient particle filtering framework for indoor localization in wireless sensor network (WSN) which searches effective anchors and constructs particle filter dynamically. Within this framework, three algorithms are integrated into the dynamic particle filter: anchor selection algorithm, location constraint resampling and SIR particle filter. The proposed scheme searches the maximum number of anchors with line of sight (LOS) to the target to guarantee the effective measurement. Then, we construct a dynamic particle filter with the chosen anchors and develop a novel resampling scheme which generates the particles within the indoor location constraints. The proposed scheme is proved to be robust and computational efficient. Simulation results show that our scheme is accurate with low computation cost, which is promising for real-time implementation.

Published in:

Positioning Navigation and Communication (WPNC), 2012 9th Workshop on

Date of Conference:

15-16 March 2012