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Title: Sequential optimal positioning of mobile sensors using mutual information

Journal Article · · Statistical Analysis and Data Mining
DOI:https://doi.org/10.1002/sam.11431· OSTI ID:1548374

Abstract Source localization, such as detecting a nuclear source in an urban area or ascertaining the origin of a chemical plume, is generally regarded as a well‐documented inverse problem; however, optimally placing sensors to collect data for such problems is a more challenging task. In particular, optimal sensor placement—that is, measurement locations resulting in the least uncertainty in the estimated source parameters—depends on the location of the source, which is typically unknown a priori . Mobile sensors are advantageous because they have the flexibility to adapt to any given source position. While most mobile sensor strategies designate a trajectory for sensor movement, we instead employ mutual information, based on Shannon entropy, to choose the next measurement location from a discrete set of design conditions.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC52-07NA27344; DE‐AC52‐07NA27344; DE‐AC05‐00O
OSTI ID:
1548374
Alternate ID(s):
OSTI ID: 1543170
Report Number(s):
LLNL-JRNL-753008; 939255
Journal Information:
Statistical Analysis and Data Mining, Vol. 12, Issue 6; ISSN 1932-1864
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

References (19)

Coverage Control for Mobile Sensing Networks journal April 2004
Hybrid optimization and Bayesian inference techniques for a non-smooth radiation detection problem: INFERENCE TECHNIQUES FOR A RADIATION DETECTION PROBLEM
  • Ştefănescu, Răzvan; Schmidt, Kathleen; Hite, Jason
  • International Journal for Numerical Methods in Engineering, Vol. 111, Issue 10 https://doi.org/10.1002/nme.5491
journal February 2017
An urban environment simulation framework for evaluating novel distributed radiation detection architectures conference November 2010
Mobility improves coverage of sensor networks conference January 2005
Evaluation of a Puff Dispersion Model in Complex Terrain journal March 1992
Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant journal January 2017
Detection and parameter estimation of multiple radioactive sources conference July 2007
An Information-Theoretic Approach to Optimally Calibrate Approximate Models conference November 2012
False Discovery Rate Based Sensor Decision Rules for the Network-Wide Distributed Detection Problem journal July 2011
Bayesian experimental design for the active nitridation of graphite by atomic nitrogen journal January 2012
Sensors on patrol (SOP): using mobile sensors to detect potential airborne nuclear, biological, and chemical attacks conference January 2005
The spread of smoke and gases from chimneys journal January 1936
Estimating mutual information journal June 2004
Maximizing the Information Content of Experiments in Systems Biology journal January 2013
Global risk from the atmospheric dispersion of radionuclides by nuclear power plant accidents in the coming decades journal January 2014
Inverse calculation approaches for source determination in hazardous chemical releases journal July 2011
An information theoretic approach to use high-fidelity codes to calibrate low-fidelity codes journal November 2016
Coverage control for mobile sensing networks conference January 2002
Bayesian experimental design for the active nitridation of graphite by atomic nitrogen preprint January 2011

Cited By (1)

Application and Evaluation of Surrogate Models for Radiation Source Search journal December 2019

Figures / Tables (9)


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