Sensor configuration and activation for field detection in large sensor arrays

Youngchul Sung; Xin Zhang; Lang Tong; H. Vincent Poor

doi:10.1109/TSP.2007.907859

Sensor configuration and activation for field detection in large sensor arrays

Youngchul Sung, Xin Zhang, Lang Tong, H. Vincent Poor

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

The problem of sensor configuration for the detection of correlated random fields using large sensor arrays is considered. Using error exponents that characterize the asymptotic behavior of the optimal detector, the detection performance of different sensor configurations is analyzed and compared. The dependence of the optimal configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection in various operating conditions. Simulation results validate the analysis based on asymptotic results for finite sample cases.

Original language	English (US)
Pages (from-to)	447-463
Number of pages	17
Journal	IEEE Transactions on Signal Processing
Volume	56
Issue number	2
DOIs	https://doi.org/10.1109/TSP.2007.907859
State	Published - Feb 2008

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering

Keywords

Correlated signal
Error exponent
Gauss and Markov field
Neyman and Pearson detection
Optimal sampling
Sensor configuration

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10.1109/TSP.2007.907859

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title = "Sensor configuration and activation for field detection in large sensor arrays",

abstract = "The problem of sensor configuration for the detection of correlated random fields using large sensor arrays is considered. Using error exponents that characterize the asymptotic behavior of the optimal detector, the detection performance of different sensor configurations is analyzed and compared. The dependence of the optimal configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection in various operating conditions. Simulation results validate the analysis based on asymptotic results for finite sample cases.",

keywords = "Correlated signal, Error exponent, Gauss and Markov field, Neyman and Pearson detection, Optimal sampling, Sensor configuration",

author = "Youngchul Sung and Xin Zhang and Lang Tong and Poor, {H. Vincent}",

note = "Funding Information: Manuscript received December 3, 2006; revised June 1, 2007. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Hongbin Li. This work was supported in part by the Army Research Office under Grant ARO-W911NF-06-1-0346 and the National Science Foundation under Contract CNS-0435190. The work of X. Zhang and H. V. Poor was also supported in part by the Air Force Research Laboratory under Cooperative Agreement FA8750-06-1-0252 and the Defense Advanced Research Projects Agency under Grant HR0011-06-1-0052. The work of Y. Sung was also supported in part by Brain Korea 21 Project, the School of Information Technology, KAIST.",

year = "2008",

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doi = "10.1109/TSP.2007.907859",

language = "English (US)",

volume = "56",

pages = "447--463",

journal = "IEEE Transactions on Signal Processing",

issn = "1053-587X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Sensor configuration and activation for field detection in large sensor arrays

AU - Sung, Youngchul

AU - Zhang, Xin

AU - Tong, Lang

AU - Poor, H. Vincent

N1 - Funding Information: Manuscript received December 3, 2006; revised June 1, 2007. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Hongbin Li. This work was supported in part by the Army Research Office under Grant ARO-W911NF-06-1-0346 and the National Science Foundation under Contract CNS-0435190. The work of X. Zhang and H. V. Poor was also supported in part by the Air Force Research Laboratory under Cooperative Agreement FA8750-06-1-0252 and the Defense Advanced Research Projects Agency under Grant HR0011-06-1-0052. The work of Y. Sung was also supported in part by Brain Korea 21 Project, the School of Information Technology, KAIST.

PY - 2008/2

Y1 - 2008/2

N2 - The problem of sensor configuration for the detection of correlated random fields using large sensor arrays is considered. Using error exponents that characterize the asymptotic behavior of the optimal detector, the detection performance of different sensor configurations is analyzed and compared. The dependence of the optimal configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection in various operating conditions. Simulation results validate the analysis based on asymptotic results for finite sample cases.

AB - The problem of sensor configuration for the detection of correlated random fields using large sensor arrays is considered. Using error exponents that characterize the asymptotic behavior of the optimal detector, the detection performance of different sensor configurations is analyzed and compared. The dependence of the optimal configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection in various operating conditions. Simulation results validate the analysis based on asymptotic results for finite sample cases.

KW - Correlated signal

KW - Error exponent

KW - Gauss and Markov field

KW - Neyman and Pearson detection

KW - Optimal sampling

KW - Sensor configuration

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JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

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ER -

Sensor configuration and activation for field detection in large sensor arrays

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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