Decentralized-Detection Based Mobile Multi-Target Tracking in Wireless Sensor Networks Conference Paper

abstract

• Due to the communications and energy constraints, we propose the decentralized-detection based schemes for Mobile Multi-Target Tracking (MMTT) in Wireless Sensor Networks (WSN). Our developed WSN consists of a symmetric-tree structure and a set of target detection and estimation strategies, which achieve the optimal error-exponent decay in detecting the number of the tracked targets. The increase in the target-number estimate accuracy also yields the high target-position estimate accuracy. We apply the Decentralized Probability Hypothesis Density (DPHD) filtering algorithm in deriving the global optimal threshold-levels for our proposed strategies to maximize the estimating accuracy for the positions of the tracked targets. The obtained extensive evaluation analyses validate and evaluate our proposed decentralized-detection structure of WSN and our developed target tracking strategies. 2010 IEEE.

name of conference

• 2010 IEEE International Conference on Communications

authors

• Zhang, Xi

published proceedings

• 2010 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS

author list (cited authors)

• Wei, J., & Zhang, X. i.

citation count

• 2

complete list of authors

• Wei, Jin||Zhang, Xi

publication date

• May 2010

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• 2013 National Conference on Communications, NCC 2013  Journal

keywords

• Data Fusion
• Decentralized Detection
• Distributed Probability Hypothesis Density ( Dphd) Filter
• M-ary Hypotheses
• Mobile Multi-target Tracking (mmtt)
• Target Identification
• Wireless Sensor Networks (wsn)

Digital Object Identifier (DOI)

• 10.1109/icc.2010.5502161

International Standard Book Number (ISBN) 13

• 9781424464043

start page

• 1

end page

• 5

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ficc.2010.5502161

user-defined tag

• 7 Affordable and Clean Energy