AN OPERATIONAL EFFECTIVENESS ANALYSIS ON SMALL ARMS SHOOTING PRECISION IN CLOSE QUARTERS BATTLE

Abstract

This thesis studies the impact of a rifleman’s shooting accuracy on operational effectiveness in close-quarters combat. The goal is to determine how improvements in shooting accuracy may reduce casualties, increase the probability of mission success, and potentially reduce manpower or ammunition (soldier’s load) requirements. Analysis was done using an agent-based simulation of a scenario based on a coalition company (blue force) assault on a platoon of insurgents (red force) defending an urban area. A full factorial design was used to generate data, the analysis of which supports the research goal. A sequential analysis campaign was devised, involving a base case analysis followed by three sets of experiments. Each experiment set was designed to inform subsequent experiments to funnel the huge combat possibilities into valuable insights. Insights from previous experiment sets guided designing the follow-on experiments to focus the desired scenario and reduce the design space. This process decreased the design space from more than 26 billion to 250,000 simulated battles. The findings from this thesis establish clear expectations and requirements for the design of next generation force structure, individual marksmanship training, shooting accuracy requirements of unmanned systems, and artificial intelligence-enabled weapons equipped to aid shooting accuracy improvements.