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Efficient communication is an essential part of cooperative work, and no less so in the case of radio communication during air combat. With time being a limited resource and the consequences of a misunderstanding potentially fatal there is little room for negligence. This work is an exploratory study which combines data mining, machine learning, natural language processing and visual analytics in an effort to investigate the possibilities of using radio traffic data from air combat simulations for human performance evaluation. Both temporal and linguistic properties of the communication were analyzed, with several promising graphical results. Additionally, utterance classification was successfully attempted with mean precision and recall both over 0.9. It is hoped that more complex and to a larger extent automated data based communication analysis can be built upon the results presented in this report. / Effektiv kommunikation är en grundläggande del av god samarbetsförmåga, inte minst när det gäller radiokommunikation under luftstrid. När tid är en begränsad resurs och ett missförstånd kan få fatala följder finns inte mycket utrymme för slarv. Det här arbetet är en utforskande studie som kombinerar data mining, maskininlärning, natural language processing och visuell dataanalys i syfte att undersöka hur radiotrafikdata från luftstridssimulering skulle kunna användas för prestationsutvärdering. Såväl tidsrelaterade som språkliga egenskaper hos kommunikationen har analyserats och flera av visualiseringarna ser lovande ut. Vidare prövades med framgång att klassificera yttranden, med genomsnittlig precision och täckning över 0.9. Förhoppningen är att de resultat som presenteras i rapporten ska kunna användas som grund för vidareutveckling av mer djupgående och i större utsträckning automatiserad databaserad kommunikationsanalys.

Small unmanned aircraft systems (sUAS) will become a disruptive force on the modern battlefield. In recent years, sUAS size and cost have decreased while their capability has increased. They have forced a reconsideration of the air superiority paradigm held since the First World War. Perhaps their most attractive, and worrisome, feature is the huge range of combat roles that they might fulfill. The presence of sUAS on future battlefields is certain, but the role they will play and their impact on those battlefields are not. This work presents a decision support framework for sUAS deployment in small infantry units. The framework is designed to explore and evaluate multiple sUAS-small-unit deployment concepts' impact on small unit effectiveness in a combat scenario of interest. The framework helps decision makers identify high-level sUAS deployment principles for testing and validation in physical experiments before sUAS are implemented on the battlefield. The decision support framework comprises the following: 1) a definition of the sUAS-small-unit deployment concept design space and combat scenario, 2) an agent-based computer model for exploring sUAS deployment concepts, 3) a set of analysis tools for evaluating sUAS deployment impact on combat effectiveness, and 4) suggestions for synthesizing high-level sUAS deployment principles from the analysis. In this work, the decision support framework for sUAS-small-unit deployment is used to explore and evaluate the impact of deploying an infantry platoon with between one and nine unmanned aerial vehicles (UAV) operating in a reconnaissance role while executing one of several sUAS patrol pattern variants. In a scenario in which a defending platoon uses sUAS to intercept and aid in indirect fires targeting against a platoon of attacking infantry, the sUAS were shown to markedly improve the defending platoon's combat effectiveness. The framework is used to synthesize several key principles for sUAS deployment in the scenario. It shows that, when fewer UAVs are deployed, short-range sUAS patrols improve defender combat effectiveness. Conversely, when more UAVs are deployed, long-range sUAS patrols improve the defenders' ability to target attacking units with indirect fires, increasing the firepower concentrated against opponents. The analysis also shows that increasing the number of deployed UAVs improves the likelihood of defending warfighters surviving the engagement and the defenders' ability to detect and engage the attackers with indirect fires. Finally, the framework shows that sUAS can force alterations in attacker behavior, removing them from combat by non-violent, but highly effective, means.

In the emerging industry of small unmanned vehicles, pioneered by small businesses and research institutions, a suitable combat system test platform is needed. Computer simulations are useful, but do not provide the definitive proof of effective operation necessary for deployment of a combat system. What is needed is an affordable simulated weapons system that enables live flight testing without the used of live weaponry. A framework is developed here for the construction of a simulated weapon using Free Space Optical (FSO) infrared communication. It is developed in such a way to ensure compatibility with a variety of platforms including ground and aerial vehicles, so that identical but configurable modules can be used on any vehicle that is to take place in a live combat simulation. A proof-of-concept implementation of this modular laser combat system framework is also presented and tested. The implemented system shows the value of such a simulated weapons system and future areas of improvement are also explored.