Designing Conservative Sensor Detection Systems With Emitter Location Uncertainty

IEEE Transactions on Aerospace and Electronic Systems ◽

10.1109/taes.2017.2665058 ◽

2017 ◽

Vol 53 (2) ◽

pp. 750-761 ◽

Author(s):

Benedito J. B. Fonseca

Keyword(s):

Detection Systems ◽

Location Uncertainty ◽

Emitter Location ◽

Sensor Detection

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Designing Conservative Sensor Detection Systems With the Scan Statistic Under Emitter Location Uncertainty

IEEE Transactions on Signal and Information Processing over Networks ◽

10.1109/tsipn.2019.2942130 ◽

2019 ◽

Vol 5 (4) ◽

pp. 711-722 ◽

Author(s):

Benedito J. B. Fonseca

Keyword(s):

Scan Statistic ◽

Detection Systems ◽

Location Uncertainty ◽

Emitter Location ◽

Sensor Detection

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Optimizing Thresholds of the Scan Statistic to Improve its Worst Case Detection Performance in Sensor Detection Systems

IEEE Transactions on Signal and Information Processing over Networks ◽

10.1109/tsipn.2021.3069300 ◽

2021 ◽

pp. 1-1

Author(s):

Benedito Fonseca

Keyword(s):

Detection Performance ◽

Case Detection ◽

Scan Statistic ◽

Detection Systems ◽

Sensor Detection

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Optimum data fusion rules in distributed sensor detection systems

Proceedings of the Twenty-Second National Radio Science Conference, 2005. NRSC 2005. ◽

10.1109/nrsc.2005.194034 ◽

2005 ◽

Author(s):

A.M.A. Aziz ◽

G.M.A. Hamid

Keyword(s):

Data Fusion ◽

Fusion Rules ◽

Distributed Sensor ◽

Detection Systems ◽

Sensor Detection

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A Clustering Algorithm to Improve the Scan Statistic in Sensor Detection Systems

IEEE Access ◽

10.1109/access.2020.2965563 ◽

2020 ◽

Vol 8 ◽

pp. 10373-10389

Author(s):

Benedito J. B. Fonseca

Keyword(s):

Clustering Algorithm ◽

Scan Statistic ◽

Detection Systems ◽

Sensor Detection

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Innovative technologies in optical fiber hydrogen sensor detection systems for space applications

10.1117/12.852078 ◽

2010 ◽

Author(s):

Alex A. Kazemi

Keyword(s):

Optical Fiber ◽

Hydrogen Sensor ◽

Space Applications ◽

Innovative Technologies ◽

Detection Systems ◽

Sensor Detection

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Least favorable distributions for the design of sensor detection systems in non-circular regions of interest

2012 IEEE Statistical Signal Processing Workshop (SSP) ◽

10.1109/ssp.2012.6319747 ◽

2012 ◽

Author(s):

Benedito J. B. Fonseca ◽

John A. Gubner

Keyword(s):

Regions Of Interest ◽

Detection Systems ◽

Sensor Detection

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Optimal data fusion strategies using multiple-sensor detection systems

Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136) ◽

10.1109/acssc.1997.680582 ◽

2002 ◽

Author(s):

A.M. Aziz ◽

M. Tummala ◽

R. Cristi

Keyword(s):

Data Fusion ◽

Detection Systems ◽

Multiple Sensor ◽

Sensor Detection

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An algorithm for global optimization of distributed multiple-sensor detection systems using Neyman-Pearson strategy

Signal Processing ◽

10.1016/0165-1684(96)00038-2 ◽

1996 ◽

Vol 51 (2) ◽

pp. 137-145 ◽

Author(s):

M.H. Elayadi ◽

Ashraf Mamdouh ◽

A.E. Basiony

Keyword(s):

Global Optimization ◽

Detection Systems ◽

Multiple Sensor ◽

Sensor Detection

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A Simpler Method To Build Nonintersecting Cluster Sets to Compute Lower Bounds for the Probability of Detection of Sensor Detection Systems using the Scan Statistic

2020 IEEE International Conference on Electro Information Technology (EIT) ◽

10.1109/eit48999.2020.9208249 ◽

2020 ◽

Author(s):

Benedito J. B. Fonseca

Keyword(s):

Lower Bounds ◽

Probability Of Detection ◽

Scan Statistic ◽

Detection Systems ◽

Cluster Sets ◽

Sensor Detection ◽

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Optimal data fusion of correlated local decisions in multiple sensor detection systems

IEEE Transactions on Aerospace and Electronic Systems ◽

10.1109/7.256317 ◽

1992 ◽

Vol 28 (3) ◽

pp. 916-920 ◽

Author(s):

M. Kam ◽

Q. Zhu ◽

W.S. Gray

Keyword(s):

Data Fusion ◽

Detection Systems ◽

Multiple Sensor ◽

Sensor Detection

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