Cart (Loading....) | Create Account
Close category search window
 

Radio Map Filter for Sensor Network Indoor Localization Systems

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)
Yong Wu ; Peking Univ., Beijing ; Jianbin Hu ; Zhong Chen

Sensor Network Indoor Localization Systems (SNILS) gain a significant attention these years, due to their ease of deployment and inexpensiveness. Ranging methods play basic role in the localization system, in which the RSSI (received signal strength indicator)-based ranging technique attracts the most attention. But the accuracy of the RSSI-based localization method remains a big challenge, because of the severe fading effects in the indoor environment. In this paper, a radio map method is proposed to improve the accuracy of the RSSI-based SNILS. This method contains two phases. The first phase is the radio map setting up phase. The radio maps are a set of probability density functions (pdf) indicating the radio fading pattern in the concerned environment, which are setup by a cooperative target. The second phase is the target tracking phase. Position probability matrixes (PPM) are used to indicate the positions of the targets, which are calculated by refering the stored radio maps according to the real-time RSSI values. To improve the localization accuracy, a radio map based Bayesian filter is proposed to iteratively calculate the PPM to speed up the convergence of the variance. Fully distributed algorithms of the localization method and the filter are designed and are implemented in the MICA2 system. The experimental accuracy is shown to be less than 1 meter with 80% probability, much better than current RSSI-based SNILS.

Published in:

Industrial Informatics, 2007 5th IEEE International Conference on  (Volume:1 )

Date of Conference:

23-27 June 2007

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.