Sequential optimal positioning of mobile sensors using mutual information

Kathleen Schmidt; Ralph C. Smith; Jason Hite; John Mattingly; Yousry Azmy; Deepak Rajan; Ryan Goldhahn

doi:10.1002/sam.11431

Sequential optimal positioning of mobile sensors using mutual information

Kathleen Schmidt, Ralph C. Smith, Jason Hite, John Mattingly, Yousry Azmy, Deepak Rajan, Ryan Goldhahn

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

8 Scopus citations

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.

Original language	English
Pages (from-to)	465-478
Number of pages	14
Journal	Statistical Analysis and Data Mining
Volume	12
Issue number	6
DOIs	https://doi.org/10.1002/sam.11431
State	Published - Dec 1 2019
Externally published	Yes

Funding

information Consortium for Nonproliferation Enabling Capabilities, Department of Energy National Nuclear Security Adm; Lawrence Livermore National Lab LDRD Program, Project No. 17-ERD-101; U.S. Department of Energy, Contract No. DE-AC52-07NA27344; LLNL-LDRD Program, 17-ERD-101; U.S. Department of Energy by Lawrence Livermore National Laboratory, DE-AC52-07NA27344; Energy Innovation Hub, DE-AC05-00OR22725; Consortium for Advanced Simulation of Light Water Reactors, U.S. Department of Energy Contract No. DE-AC05-00O; Department of Energy National Nuclear Security Administration (NNSA), DE-NA0002576We thank Don Lucas for providing the high-fidelity tracer release data. Also, we thank Isaac Michaud and Allison Lewis for ongoing discussion regarding this problem. This research was supported in part by the Department of Energy National Nuclear Security Administration (NNSA) under the Award Number DE-NA0002576 through the Consortium for Nonproliferation Enabling Capabilities (CNEC). It was also supported by the Consortium for Advanced Simulation of Light Water Reactors (http://www.casl.gov), an Energy Innovation Hub (http://www.energy.gov/hubs) for Modeling and Simulation of Nuclear Reactors under U.S. Department of Energy Contract No. DE-AC05-00OR22725. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was supported by the LLNL-LDRD Program under Project No. 17-ERD-101. LLNL-JRNL-753008.

Funders	Funder number
Consortium for Advanced Simulation of Light Water Reactors	DE-AC05-00O
Consortium for Nonproliferation Enabling Capabilities
Energy Innovation Hub
Lawrence Livermore National Laboratory	LLNL-JRNL-753008
Modeling and Simulation of Nuclear Reactors
U.S. Department of Energy	DE-AC05-00OR22725, DE-AC52-07NA27344
National Nuclear Security Administration	DE-NA0002576
Lawrence Livermore National Laboratory	17-ERD-101

Keywords

Bayesian inference
inverse problem
mutual information
sensor placement
source localization

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10.1002/sam.11431

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Sequential optimal positioning of mobile sensors using mutual information

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