Accession Number:

ADA305669

Title:

Cluster Recognition Algorithms for Battlefield Simulation.

Descriptive Note:

Corporate Author:

OKLAHOMA UNIV NORMAN

Personal Author(s):

Report Date:

1996-01-01

Pagination or Media Count:

225.0

Abstract:

The target acquisition fire support model TAFSM is a large scale, automated, artillery combat simulation model. This model has been developed over a period of years to include increasingly large and realistic battlefield situations and still retain its efficiency. To process more complicated battlefield scenarios within time constraints, units on the battlefield must be grouped into clusters, which will then be treated as a single entity in further processing. These clusters fall into three categories circular clusters, linear clusters, and on-line clusters. To perform clustering within the time constraints, two classic clustering algorithms were modified to meet the stringent efficiency constraints. To detect circular clusters, a template-matching technique was designed. Linear and on-line clusters were found using an algorithm that has roots in the single-link clustering method. These algorithms were implemented and tested on 59 data sets from the TAFSM simulation. The new algorithms ran within a few seconds and created reasonable clusterings. AN

Subject Categories:

  • Computer Programming and Software
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE