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

Position-adaptive direction finding of electromagnetic sources using wireless sensor networks

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

5 Author(s)
Selmic, R.R. ; Dept. of Electr. Eng., Louisiana Tech Univ., Ruston, LA, USA ; Gates, M. ; Barber, C. ; Mitra, A.
more authors

Wireless sensor networks are being used in a variety of ways - from reconnaissance and detection in military to biomedical applications and a wide variety of commercial endeavors. We introduce a position-adaptive direction finding method using mobile sensor networks and present recent experimental results in localization of a non-cooperative sensor node using static and mobile sensor networks. Electromagnetic (EM) direction finding is a technique in which a group or a swarm of Micro-Aerial Vehicles (MAVs) cooperate their sensing missions, adapt their position in real-time autonomously, and localize an unknown, hidden EM source based on optimal detection algorithms. The MAVs are equipped with IRIS wireless sensor nodes that serve as the sensing agents by providing mobility to the otherwise stationary nodes. In order to localize the transmitter, we use the Received Signal Strength Indicator (RSSI) data to approximate distance from the transmitter to the revolving receivers. We provide an algorithm for on-line estimation of the Path Loss Exponent (PLE) estimation that is used in modeling the distance based on received signal strength (RSS) measurements. The emitter position estimation is calculated based on surrounding sensors RSS values using Least-Square Estimation (LSE).

Published in:

Control & Automation (MED), 2011 19th Mediterranean Conference on

Date of Conference:

20-23 June 2011

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.