Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/58354
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Type: Conference paper
Title: Distributive Target Tracking in Wireless Sensor Networks under Measurement Origin Uncertainty
Author: Ma, Y.
Ng, B.
Citation: Proceedings of the 3rd International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2007) / M. Palaniswami, S. Marusic, Y. W. Law (eds.): pp.299-304
Publisher: IEEE
Publisher Place: New York
Issue Date: 2007
ISBN: 1424415020
9781424415014
Conference Name: International Conference on Intelligent Sensors, Sensor Networks and Information Processing (3rd : 2007 : Melbourne, Victoria)
Statement of
Responsibility: 
Hui Ma, Brian W.-H. Ng
Abstract: This paper addresses the problem of tracking a single target under measurement uncertainty due to clutters and missed detections in wireless sensor networks. By adopting the particles' representation of the probability density function of target state, this paper develops a particle filter (PF) and probabilistic data association filter (PDAF) hybrid tracking algorithm, name as PF-PDAF. PF-PDAF extends the well-known PDAF to the general nonlinear system. Based on the hierarchical sensor network architecture, the distributive PF- PDAF is also implemented. Moreover, the posterior Cramer-Rao lower bound (PCRLB) is computed to provide a theoretical bound on the tracking performance of the developed algorithms. Simulation results are provided.
Rights: © 2007 IEEE
RMID: 0020095806
DOI: 10.1109/ISSNIP.2007.4496860
Appears in Collections:Electrical and Electronic Engineering publications

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