A Comparative Analysis of Ship Self Air Defense (SSAD) Systems Using a Modkit Simulation.

Abstract

Rapid changes and developments in defense technology have created a difficult analytical environment for decision authorities when selecting the best weapon system for their armed forces. Appropriate operations analysis techniques and tools can provide some insight needed for the selection process. The objective of this thesis is to identify and develop suitable Operations Research analytical techniques and tools to aid decision authorities in the Ship Self Air Defense (SSAD) system selection process. The thesis first develops a SSAD system simulation Model (SSAD-Sim) using discrete event simulation techniques and implements it in the Java programming language and Modkit. The simulation is then used to identify appropriate exploratory analysis capabilities including measures of effectiveness evaluation and parameter sensitivity analysis. Exploratory analysis techniques are used to evaluate two different SSAD systems and firing policies. Key parameters analyzed for sensitivity include numbers of trackers, SAM inventory levels and tracker slew delay. As a result of the success of the SSAD simulation, further component additions and modifications are recommended for further study and development.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1999
Accession Number
ADA361974

Entities

People

  • Bulent Turan

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Defense
  • Aircrafts
  • Anti-Ship Missiles
  • Computer Programming
  • Control Systems
  • Defense Systems
  • Detection
  • Java Programming Language
  • Language
  • Measures Of Effectiveness
  • Object Oriented Programming
  • Operations Research
  • Programming Languages
  • Radar
  • Simulations
  • Statistical Analysis
  • Weapon Systems

Readers

  • Aerospace Test and Evaluation
  • Logistics and Supply Chain Management.
  • Regression Analysis.