DocumentCode :
2938260
Title :
A Hierarchical Multiple-Target Tracking Algorithm for Sensor Networks
Author :
Oh, Songhwai ; Sastry, Shankar ; Schenato, Luca
Author_Institution :
Dept. of EECS University of California, Berkeley Berkeley, CA 94720, U.S.A. sho@eecs.berkeley.edu
fYear :
2005
fDate :
18-22 April 2005
Firstpage :
2197
Lastpage :
2202
Abstract :
Multiple-target tracking is a canonical application of sensor networks as it exhibits different aspects of sensor networks such as event detection, sensor information fusion, multi-hop communication, sensor management and decision making. The task of tracking multiple objects in a sensor network is challenging due to constraints on a sensor node such as short communication and sensing ranges, a limited amount of memory and limited computational power. In addition, since a sensor network surveillance system needs to operate autonomously without human operators, it requires an autonomous tracking algorithm which can track an unknown number of targets. In this paper, we develop a scalable hierarchical multiple-target tracking algorithm that is autonomous and robust against transmission failures, communication delays and sensor localization error.
Keywords :
Markov chain Monte Carlo; Sensor networks; data association; multiple-target tracking; Computer network management; Computer networks; Decision making; Event detection; Power system management; Sensor fusion; Sensor systems; Spread spectrum communication; Surveillance; Target tracking; Markov chain Monte Carlo; Sensor networks; data association; multiple-target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on
Print_ISBN :
0-7803-8914-X
Type :
conf
DOI :
10.1109/ROBOT.2005.1570439
Filename :
1570439
Link To Document :
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