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Detection and Tracking Using Particle-Filter-Based Wireless Sensor Networks
September 2010 (vol. 9 no. 9)
pp. 1332-1345
ASCII Text
x 
 
Nadeem Ahmed, Mark Rutten, Travis Bessell, Salil S. Kanhere, Neil Gordon, Sanjay Jha, "Detection and Tracking Using Particle-Filter-Based Wireless Sensor Networks," IEEE Transactions on Mobile Computing, vol. 9, no. 9, pp. 1332-1345, September, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TMC.2010.83,
author = {Nadeem Ahmed and Mark Rutten and Travis Bessell and Salil S. Kanhere and Neil Gordon and Sanjay Jha},
title = {Detection and Tracking Using Particle-Filter-Based Wireless Sensor Networks},
journal ={IEEE Transactions on Mobile Computing},
volume = {9},
number = {9},
issn = {1536-1233},
year = {2010},
pages = {1332-1345},
doi = {http://doi.ieeecomputersociety.org/10.1109/TMC.2010.83},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Mobile Computing
TI - Detection and Tracking Using Particle-Filter-Based Wireless Sensor Networks
IS - 9
SN - 1536-1233
SP1332
EP1345
EPD - 1332-1345
A1 - Nadeem Ahmed,
A1 - Mark Rutten,
A1 - Travis Bessell,
A1 - Salil S. Kanhere,
A1 - Neil Gordon,
A1 - Sanjay Jha,
PY - 2010
KW - Wireless sensor networks
KW - simulations
KW - experiments
KW - performance attributes
KW - measurements.
VL - 9
JA - IEEE Transactions on Mobile Computing
ER -
 
Nadeem Ahmed, University of New South Wales, Sydney, Australia
Mark Rutten, Defense Science and Technology Organization, Edinburgh, Australia
Travis Bessell, Defense Science and Technology Organization, Edinburgh, Australia
Salil S. Kanhere, University of New South Wales, Sydney, Australia
Neil Gordon, Defense Science and Technology Organization, Edinburgh, Australia
Sanjay Jha, University of New South Wales, Sydney, Australia
The work reported in this paper investigates the performance of the Particle Filter (PF) algorithm for tracking a moving object using a wireless sensor network (WSN). It is well known that the PF is particularly well suited for use in target tracking applications. However, a comprehensive analysis on the effect of various design and calibration parameters on the accuracy of the PF has been overlooked. This paper outlines the results from such a study. In particular, we evaluate the effect of various design parameters (such as the number of deployed nodes, number of generated particles, and sampling interval) and calibration parameters (such as the gain, path loss factor, noise variations, and nonlinearity constant) on the tracking accuracy and computation time of the particle-filter-based tracking system. Based on our analysis, we present recommendations on suitable values for these parameters, which provide a reasonable trade-off between accuracy and complexity. We also analyze the theoretical Cramér-Rao Bound as the benchmark for the best possible tracking performance and demonstrate that the results from our simulations closely match the theoretical bound. In this paper, we also propose a novel technique for calibrating off-the-shelf sensor devices. We implement the tracking system on a real sensor network and demonstrate its accuracy in detecting and tracking a moving object in a variety of scenarios. To the best of our knowledge, this is the first time that empirical results from a PF-based tracking system with off-the-shelf WSN devices have been reported. Finally, we also present simple albeit important building blocks that are essential for field deployment of such a system.

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Index Terms:
Wireless sensor networks, simulations, experiments, performance attributes, measurements.
Citation:
Nadeem Ahmed, Mark Rutten, Travis Bessell, Salil S. Kanhere, Neil Gordon, Sanjay Jha, "Detection and Tracking Using Particle-Filter-Based Wireless Sensor Networks," IEEE Transactions on Mobile Computing, vol. 9, no. 9, pp. 1332-1345, Sept. 2010, doi:10.1109/TMC.2010.83
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