Rule-based multiple-target tracking in acoustic wireless sensor networks

被引:12
作者
An, Youngwon Kim [1 ]
Yoo, Seong-Moo [2 ]
An, Changhyuk [1 ]
Wells, B. Earl [2 ]
机构
[1] AnMathTek, Huntsville, AL 35803 USA
[2] Univ Alabama, Dept Elect & Comp Engn, Huntsville, AL 35899 USA
关键词
Wireless sensor networks; Doppler effect; Kalman filter; Track association; Multiple targets; MULTITARGET TRACKING; DATA ASSOCIATION; LOCALIZATION; CLASSIFICATION;
D O I
10.1016/j.comcom.2014.05.011
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper introduces an efficient rule-based algorithm for tracking multiple fast-moving ground vehicles in an acoustic Wireless Sensor Network (WSN). To reduce the level of power consumption, the acoustic sensor nodes in the WSN are assumed to be very simple in nature, having no capability to discern the direction and range of targets or to communicate directly with adjacent peer nodes. Instead the WSN employs a specialized fusion center that collects detection information directly from the sensor nodes. Accurate tracking of multiple high-speed targets can be affected by the Doppler shift and by the merging and splitting of target trajectories. To satisfy all of these requirements for target tracking in acoustic WSNs, a rule-based low-complexity tracking algorithm is presented in this work. The algorithm performs clustering of the detecting sensors and computes the weighted centroid of each cluster to determine the number of targets and their positions. The algorithm also takes into account the target path merging and splitting that necessitates cluster-to-cluster associations as well as detection-to-track associations. The algorithm compensates for the Doppler effect, has a relatively low computational complexity, and has been shown to have high overall track accuracy. (c) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:81 / 94
页数:14
相关论文
共 48 条
[1]   Detection and Tracking Using Particle-Filter-Based Wireless Sensor Networks [J].
Ahmed, Nadeem ;
Rutten, Mark ;
Bessell, Travis ;
Kanhere, Salil S. ;
Gordon, Neil ;
Jha, Sanjay .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2010, 9 (09) :1332-1345
[2]  
An Y.K., 2012, P 25 INT C COMP APPL, P151
[3]   Noise Mitigation for Target Tracking in Wireless Acoustic Sensor Networks [J].
An, Youngwon Kim ;
Yoo, Seong-Moo ;
An, Changhyuk ;
Wells, Earl .
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2013, 7 (05) :1166-1179
[4]   Doppler effect on target tracking in wireless sensor networks [J].
An, Youngwon Kim ;
Yoo, Seong-Moo ;
An, Changhyuk ;
Wells, B. Earl .
COMPUTER COMMUNICATIONS, 2013, 36 (07) :834-848
[5]   Distributed target classification and tracking in sensor networks [J].
Brooks, RR ;
Ramanathan, P ;
Sayeed, AM .
PROCEEDINGS OF THE IEEE, 2003, 91 (08) :1163-1171
[6]   On collaborative tracking of a target group using binary proximity sensors [J].
Cao, Donglei ;
Jin, Beihong ;
Das, Sajal K. ;
Cao, Jiannong .
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2010, 70 (08) :825-838
[7]   Dynamic clustering for acoustic target tracking in wireless sensor networks [J].
Chen, WP ;
Hou, JC ;
Sha, L .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2004, 3 (03) :258-271
[8]   On Energy Efficiency in Collaborative Target Tracking in Wireless Sensor Network: A Review [J].
Demigha, Oualid ;
Hidouci, Walid-Khaled ;
Ahmed, Toufik .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2013, 15 (03) :1210-1222
[9]   Target tracking by particle filtering in binary sensor networks [J].
Djuric, Petar M. ;
Vemula, Mahesh ;
Bugallo, Monica F. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2008, 56 (06) :2229-2238
[10]  
Djuric PM, 2004, IEEE 11TH DIGITAL SIGNAL PROCESSING WORKSHOP & 2ND IEEE SIGNAL PROCESSING EDUCATION WORKSHOP, P263