Artificial intelligence to assist ground troop formation identification though tactical tracks

Kirsten McCormick; Paul Freeman

doi:10.1117/12.2662197

12 June 2023 Artificial intelligence to assist ground troop formation identification though tactical tracks

Kirsten McCormick, Paul Freeman

Proceedings Volume 12544, Open Architecture/Open Business Model Net-Centric Systems and Defense Transformation 2023; 125440O (2023) https://doi.org/10.1117/12.2662197
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

The Ground Troop Formation Identification research demonstrates how Machine Learning (ML) can be employed to classify ground force formations from the mass of individual observations made by local sensors and tactical information received from the connected battlespace at 93.75% accuracy at inference. This research examined suitable Machine Learning options, resulting in the development of a Random Forest (RF) algorithm software solution that was then integrated with a representative airborne mission system environment consisting of a Data Link Processor (DLP) and a Tactical HMI. This allowed a more realistic testing of how it could perform in a real world environment. This research displayed the results within a platforms tactical HMI for clear presentation. This system would aid an already burdened operator by automatically performing the complicated task of quick and effective Tactical Situational Awareness (SA) analysis, securing operational advantage through improved speed, accuracy and quality of decision making.

Conference Presentation

Citation Download Citation

Kirsten McCormick and Paul Freeman "Artificial intelligence to assist ground troop formation identification though tactical tracks", Proc. SPIE 12544, Open Architecture/Open Business Model Net-Centric Systems and Defense Transformation 2023, 125440O (12 June 2023); https://doi.org/10.1117/12.2662197

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