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Optimization of steerable sensor network for threat detection

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  • Anton Molyboha
  • Michael Zabarankin

Abstract

A Markov chain approach to detecting a threat in a given surveillance zone by a network of steerable sensors is presented. The network has a finite number of predetermined states, and transition from one state to another follows a Markov chain. Under the assumption that the threat avoids detection, two game theoretic problems for finding an optimal Markov chain (two surveillance strategies) are formulated: the first maximizes the probability of threat detection for two consecutive detection periods, whereas the second minimizes the average time of detection for the worst‐case threat's trajectory. Both problems are reduced to linear programming, and special techniques are suggested to solve them. For a dynamic environment with moving noise sources, the optimal Markov chain changes at each detection period, and the rate of convergence of the Markov chain to its stationary distribution is analyzed. Both surveillance strategies are tested in numerical experiments and compared one with another. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011

Suggested Citation

  • Anton Molyboha & Michael Zabarankin, 2011. "Optimization of steerable sensor network for threat detection," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(6), pages 564-577, September.
  • Handle: RePEc:wly:navres:v:58:y:2011:i:6:p:564-577
    DOI: 10.1002/nav.20467
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    References listed on IDEAS

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    1. Sergei Pashko & Anton Molyboha & Michael Zabarankin & Sergei Gorovyy, 2008. "Optimal sensor placement for underwater threat detection," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 684-699, October.
    2. Baxter, J. R. & Rosenthal, Jeffrey S., 1995. "Rates of convergence for everywhere-positive Markov chains," Statistics & Probability Letters, Elsevier, vol. 22(4), pages 333-338, March.
    3. Dipesh J. Patel & Rajan Batta & Rakesh Nagi, 2005. "Clustering Sensors in Wireless Ad Hoc Networks Operating in a Threat Environment," Operations Research, INFORMS, vol. 53(3), pages 432-442, June.
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