A Markov analysis of the cueing capability/detection rate trade-space in search and rescue

Abstract

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. © 2007 Springer-Verlag Berlin Heidelberg.