By Topic

Algorithm for Detection with Localization of Multi-targets in Wireless Acoustic 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

4 Author(s)
Jaechan Lim ; Dept. of Electr. & Comput. Eng., State Univ. of New York, Stony Brook, NY ; Jinseok Lee ; Sangjin Hong ; Peom Park

In most multitarget tracking approaches based on joint probabilistic data association (JPDA), it is difficult to apply the solutions to problems (due to the dimensionality curse of heavy complexity) where the number of target varies dramatically. In this paper, we introduce an algorithm for detection of multitargets in wireless acoustic sensor networks (ADMAN); we localize detected targets by particle filtering after ADMAN. The purpose of ADMAN is detecting any number of targets (We know the approximate locations of targets during the detection algorithm.) in the field of interest. The advantage of ADMAN is its ability to cope with varying number of targets in time. ADMAN does not have any restrictions on the varying pattern of the target number

Published in:

Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on

Date of Conference:

Nov. 2006