Date of Award

3-2021

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Systems Engineering and Management

First Advisor

David R. Jacques, PhD

Abstract

Autonomous munitions provide an opportunity for the Department of Defense (DoD) to extend the capabilities of operators in combat situations. However, there is also a need for a high level of trust in the effectiveness and accuracy of these systems. With the advent of model-based standards in autonomy and munitions, there is a need to implement these techniques toward an effective modeling and simulation (MS) capability. By leveraging modern MS tools such as Cameo Systems Modeler and the DoD's Advanced Framework for Simulation, Integration, and Modeling (AFSIM), this thesis proposes a framework for simulating complex autonomy architectures within high fidelity simulation environments. Building on this proposed framework, a state-based behavioral model was developed that captures a collaborative autonomous munition within the context of a Suppression of Enemy Air Defenses (SEAD) mission. This system model shows the ability for Cameo to host interactive, executable state machines and demonstrate autonomous decision making based on internal system and environmental cues in order to generate mission effectiveness performance measures.

AFIT Designator

AFIT-ENV-MS-21-M-245

DTIC Accession Number

AD1138300

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