Channel aware particle filtering for tracking in sensor networks

Onur Ozdemir; Ruixin Niu; Pramod K. Varshney

doi:10.1109/ACSSC.2006.356634

Channel aware particle filtering for tracking in sensor networks

Onur Ozdemir, Ruixin Niu, Pramod K. Varshney

Department of Electrical Engineering & Computer Science

Research output: Chapter in Book/Entry/Poem › Conference contribution

9 Scopus citations

Abstract

Due to recent advances in computation power, particle filtering has become a very promising tool for nonlinear non-Gaussian tracking applications. In this paper, a new framework for target tracking in a wireless sensor network using particle filtering is proposed. Under this framework, the imperfect nature of the communication channels between sensors and the fusion center is taken into account, and the channel information as well as inherent limitations of wireless sensors are incorporated in the tracking algorithm based on particle filters. Simulation results are presented to demonstrate the superior performance of the proposed algorithm.

Original language	English (US)
Title of host publication	Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages	290-294
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2006.356634
State	Published - 2006
Event	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States Duration: Oct 29 2006 → Nov 1 2006

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)	1058-6393

Other

Other	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
Country/Territory	United States
City	Pacific Grove, CA
Period	10/29/06 → 11/1/06

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2006.356634

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Channel aware particle filtering for tracking in sensor networks. / Ozdemir, Onur; Niu, Ruixin; Varshney, Pramod K.
Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06. 2006. p. 290-294 4176563 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

Research output: Chapter in Book/Entry/Poem › Conference contribution

Ozdemir, O, Niu, R & Varshney, PK 2006, Channel aware particle filtering for tracking in sensor networks. in Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06., 4176563, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 290-294, 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06, Pacific Grove, CA, United States, 10/29/06. https://doi.org/10.1109/ACSSC.2006.356634

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abstract = "Due to recent advances in computation power, particle filtering has become a very promising tool for nonlinear non-Gaussian tracking applications. In this paper, a new framework for target tracking in a wireless sensor network using particle filtering is proposed. Under this framework, the imperfect nature of the communication channels between sensors and the fusion center is taken into account, and the channel information as well as inherent limitations of wireless sensors are incorporated in the tracking algorithm based on particle filters. Simulation results are presented to demonstrate the superior performance of the proposed algorithm.",

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AB - Due to recent advances in computation power, particle filtering has become a very promising tool for nonlinear non-Gaussian tracking applications. In this paper, a new framework for target tracking in a wireless sensor network using particle filtering is proposed. Under this framework, the imperfect nature of the communication channels between sensors and the fusion center is taken into account, and the channel information as well as inherent limitations of wireless sensors are incorporated in the tracking algorithm based on particle filters. Simulation results are presented to demonstrate the superior performance of the proposed algorithm.

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Channel aware particle filtering for tracking in sensor networks

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