A Markov Analysis of the Cueing Capability/Detection Rate Trade-space in Search and Rescue

Alice M. Alexander () and David E. Jeffcoat ()
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Alice M. Alexander: Munitions Directorate
David E. Jeffcoat: Munitions Directorate

A chapter in Cooperative Systems, 2007, pp 185-196 from Springer

Abstract: Summary This chapter presents a search and rescue scenario modeled as a discrete-state, continuous-time Markov process. In this scenario, there are two vehicle types: search-only vehicles capable of searching for persons in distress, but not engaging or rescuing them, and search-and-engage vehicles with the capability both to search and to rescue. All vehicles have two-way communication with other vehicles. Both vehicle types can search independently, but information provided by other vehicles improves their detection capability. We develop a Markov model and use matrix exponentiation to numerically determine the transient state probabilities for the system. We use as a measure of effectiveness the time required for at least two search-and-engage vehicles to arrive on scene with a threshold probability. We then analyze the trade-space between cueing capability and vehicle detection rates.

Keywords: Markov Chain; Detection Rate; Markov Chain Model; Vehicle Type; Continuous Time Markov Chain (search for similar items in EconPapers)
Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-540-48271-0_12

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DOI: 10.1007/978-3-540-48271-0_12

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