MRI: Track 2 Development of a Multi-Sensor Data Acquisition Remote Tower System to Enable Research for Safe and Secure Airspace Management

This Major Research Instrumentation (MRI) award supports the development of an integrated airspace sensing and analysis system at the Kent State University Airport and the Kent State University College of Aeronautics and Engineering training facilities. The national airspace is becoming increasingly complex as crewed aircraft, uncrewed aerial systems, autonomous vehicles, and small aircraft operate in shared environments. Safe management of this emerging airspace requires new instrumentation capable of collecting, integrating, and analyzing high-fidelity data about aircraft location, motion, behavior, and operating conditions. Current air traffic monitoring systems were not designed to support the scale, resolution, and flexibility needed to study mixed crewed and uncrewed operations, especially in airport environments where low-altitude traffic, small uncrewed aircraft, and autonomous systems may interact. The instrument will provide a unique research and training capability by integrating multiple sensing modalities, including infrared and LiDAR sensors, with data storage, processing, and visualization tools. The system will generate a unified data stream that can support detection, tracking, identification, and analysis of cooperative and non-cooperative aircraft, including small uncrewed aerial systems. This capability will allow researchers and students to study how sensing systems, data architectures, decision-support tools, and operational procedures can be designed and integrated to improve airspace safety, resilience, and performance. The instrument will also support research on system architecture, sensor fusion, requirements analysis, risk-informed decision-making, human-system interaction, autonomous operations, secure data management, and verification and validation of advanced airspace management concepts. The primary objective of the research program enabled by this instrument is to advance multi-sensor, data-driven engineering methods for safe and reliable management of increasingly complex airspace. The instrument will provide high-resolution data needed to evaluate and improve models of airspace behavior, sensor performance, aircraft detection and tracking, and autonomous system integration. These data will support the development and validation of system architectures and cybersecurity for future air traffic management environments that include both crewed and uncrewed aircraft. By combining physical sensing infrastructure with data management and analysis capabilities, the instrument will enable researchers to evaluate tradeoffs among sensing fidelity, operational safety, system responsiveness, data accessibility, and resilience under varied environmental and operational conditions. The instrument will also strengthen education and workforce development in aeronautics, aerospace engineering, systems engineering, and autonomous systems. Students will gain hands-on experience with real-world airspace data, sensor integration, system architecture, risk analysis, and decision-support methods. The system will support undergraduate and graduate research, laboratory instruction, industry collaboration, and training activities focused on the design and operation of safe, reliable, and resilient airspace systems. External researchers and collaborators will be able to access selected data and capabilities through appropriate authorization mechanisms, expanding the impact of the instrument beyond Kent State University. The broader impact of this work includes preparing the future aviation workforce and supporting research that can inform safe integration of uncrewed and autonomous systems into airport and airspace operations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.