Visible to the public A C4ISR Application on the Swarm Drones Context in a Low Infrastructure Scenario

TitleA C4ISR Application on the Swarm Drones Context in a Low Infrastructure Scenario
Publication TypeConference Paper
Year of Publication2022
AuthorsFigueira, Nina, Pochmann, Pablo, Oliveira, Abel, de Freitas, Edison Pignaton
Conference Name2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)
Date Publishedjul
KeywordsAmazon Scenario, autonomous aerial vehicles, C4ISR, human factors, IFA2S, INTERC2, iobt, Low Infrastructure Scenario, MOSA, pubcrawl, Reconnaissance, resilience, Resiliency, Safety, Scalability, SDR, sensor fusion, Sensor systems, surveillance, Swarm Drones, Topology
AbstractThe military operations in low communications infrastructure scenarios employ flexible solutions to optimize the data processing cycle using situational awareness systems, guaranteeing interoperability and assisting in all processes of decision-making. This paper presents an architecture for the integration of Command, Control, Computing, Communication, Intelligence, Surveillance and Reconnaissance Systems (C4ISR), developed within the scope of the Brazilian Ministry of Defense, in the context of operations with Unmanned Aerial Vehicles (UAV) - swarm drones - and the Internet-to-the-battlefield (IoBT) concept. This solution comprises the following intelligent subsystems embedded in UAV: STFANET, an SDN-Based Topology Management for Flying Ad Hoc Network focusing drone swarms operations, developed by University of Rio Grande do Sul; Interoperability of Command and Control (INTERC2), an intelligent communication middleware developed by Brazilian Navy; A Mission-Oriented Sensors Array (MOSA), which provides the automatization of data acquisition, data fusion, and data sharing, developed by Brazilian Army; The In-Flight Awareness Augmentation System (IFA2S), which was developed to increase the safety navigation of Unmanned Aerial Vehicles (UAV), developed by Brazilian Air Force; Data Mining Techniques to optimize the MOSA with data patterns; and an adaptive-collaborative system, composed of a Software Defined Radio (SDR), to solve the identification of electromagnetic signals and a Geographical Information System (GIS) to organize the information processed. This research proposes, as a main contribution in this conceptual phase, an application that describes the premises for increasing the capacity of sensing threats in the low structured zones, such as the Amazon rainforest, using existing communications solutions of Brazilian defense monitoring systems.
Citation Keyfigueira_c4isr_2022