Accession Number:

ADA331679

Title:

Stochastic and Deterministic Models of Targeting, with Dynamic and Error-Prone BDA

Descriptive Note:

Technical rept.

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF OPERATIONS RESEARCH

Report Date:

1997-09-01

Pagination or Media Count:

41.0

Abstract:

Deep precision strike is a generic military operation that depends importantly on C4ISR system contributions. Information from the latter is realistically subject to chance influences targets are found and correctly identified generally at rates proportional to their numbers, locations, and activities, and to the coverage of shooter-serving sensors the events of detection are realistically random, as are the delays, results, outcomes, and follow-up of the targeting shooters. In this paper a simplified version of the above complicated process is analyzed mathematically, here as a multi-stage queuing process with imperfect service. The probabilistic outcomes can be used to anticipate the results of higher-resolution simulations these often are far more time consuming both to set up and run. Aspects of the above queuing situations can also be deduced via a deterministic fluid queuing approximation that gives an adequate and convenient representation of aspects of the state variables and various Measures of Effectiveness in the stochastic queuing model. Relying on that agreement, we have elsewhere generalized the stochastic queuing model setup to fluid models that incorporate omitted realities, such as losses from target-list tracking, and the inevitable time dependencies, non-stationarities, and adaptive behaviors that typically occur in actual military operations or vignettes. Both the stochastic and deterministic model results are informative and produce reasonable insights. Further validation steps using mathematical probability techniques as well as simulation are planned some are in progress.

Subject Categories:

  • Operations Research
  • Military Operations, Strategy and Tactics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE