By Topic

Passive multi-object localization and tracking using bearing data

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)
Schikora, M. ; Sensor Data & Inf. Fusion Dept., Fraunhofer FKIE, Wachtberg, Germany ; Bender, D. ; Cremers, D. ; Koch, W.

This paper addresses the problem of localization and tracking multiple non-cooperative objects using only passive bearing sensor data. The challenges in this context lie in an unknown number of objects, false alarms and clutter measurements. To avoid the time consuming data association and data storage, an iterative approach, which only considers the sensor data from the actual timestep for an update of every object state, is preferable. Our approach to perform this is a Monte Carlo realization of a probability hypothesis density filter. In this context we use bearing data gained from an antenna or optical camera mounted on an airborne observer. Tests on simulated and real world scenarios show that our approach leads to a stable localization and tracking of multiple targets, even in the presence of clutter and misleading bearing measurements.

Published in:

Information Fusion (FUSION), 2010 13th Conference on

Date of Conference:

26-29 July 2010