In the near future, unmanned aerial vehicles (UAVs), commonly known as drones, will become ubiquitous in the skies above populated areas, serving millions worldwide in goods transportation, construction, agriculture, medical services, surveillance, search-and-rescue operations, and many other applications. Autonomous UAVs will perform daily tasks such as food and package delivery, grocery shopping, and surveillance in densely populated areas, profoundly transforming everyday human life.
The LUCAT project, funded by IKTPLUSS-INDNOR (a joint Indo-Norwegian researcher initiative in Information and Communication Technology by NFR and DST), has successfully developed technology for accurate sensing, precise tracking, and communication of both manned and unmanned aerial vehicles operating in low-altitude corridors. The Autonomous and Cyber-Physical Systems Research Group at the University of Agder, Campus Grimstad, Norway, in collaboration with the Department of Electrical Engineering, Indian Institute of Technology, Hyderabad, and the Department of Computational and Data Sciences, Indian Institute of Sciences, Bangalore, have designed, developed, and implemented the proposed technology.
Using mmWave radar sensors and other advanced sensors, along with novel signal processing and machine learning models and wireless communication algorithms, this project aimed to sense, detect, and precisely track multiple rapidly moving UAVs. New methods were developed to classify objects in flight corridors, and the communication modules within UAVs now include advanced software-defined radio capabilities to sense the radio-frequency environment dynamically, leading to the discovery of communication opportunities—referred to as spectrum cognizant communications. The integration of sensing, tracking, and communication tasks has significantly improved the performance of these functions compared to existing low-altitude traffic management systems.
Ground-station mmWave radars were used to develop new techniques for the detection, localization, and classification of UAVs. Additionally, hybrid communication schemes were explored for UAV-to-UAV and UAV-to-Ground Station communications. The successful completion of the LUCAT project represents a major advancement in the management of low-altitude air traffic, paving the way for safer and more efficient use of UAVs in various essential applications.
Outcomes:
1. Enhanced Tracking and Sensing Technology: Development of accurate sensing and tracking systems using mmWave radar sensors, signal processing, and machine learning models. Improved capability to detect, track, and classify multiple UAVs in low-altitude airspaces.
2. Advanced Communication Modules: Implementation of software-defined radio modules for real-time spectrum sensing and communication optimization (spectrum cognizant communications). Development of hybrid communication schemes for UAV-to-UAV and UAV-to-Ground Station interactions.
3. Robust Low-Altitude Traffic Management: Creation of a comprehensive system for managing low-altitude UAV traffic, integrating enhanced sensing, tracking, and communication technologies. Significant improvements in the safety and efficiency of UAV operations in populated areas.
4. Collaboration and Knowledge Sharing: Strengthened collaboration between the University of Agder (Norway) and Indian institutions (IIT Hyderabad and IISc Bangalore). Exchange of expertise and knowledge, fostering future research collaborations in autonomous systems and communication technologies.
Potential Impacts:
1. Commercial and Industrial Applications: Adoption of advanced UAV technologies in industries such as logistics, agriculture, construction, and surveillance. Increased efficiency and reliability in commercial UAV applications due to enhanced tracking and communication capabilities.
2. Public Safety and Emergency Services: Improved capabilities for search-and-rescue operations and medical deliveries, enhancing response times and effectiveness. Enhanced surveillance and monitoring for public safety, contributing to better law enforcement and disaster management.
3. Urban Air Mobility (UAM) Integration: Facilitating the integration of UAVs into urban environments, supporting initiatives like smart cities and autonomous delivery systems. Contribution to the infrastructure needed for the future of urban air mobility, including passenger drones and autonomous air taxis.
4. Regulatory and Policy Development: Providing data and insights to inform regulatory frameworks for safe UAV operations in low-altitude airspace. Assisting policymakers in developing guidelines and standards for UAV traffic management, ensuring safe and efficient airspace utilization.
5. Technological Advancements: Driving further innovation in UAV technology, particularly in areas of AI, machine learning, and wireless communications. Stimulating research and development in related fields, leading to new breakthroughs and applications.
6. Economic Growth: Boosting economic growth through the creation of new markets and job opportunities related to UAV technology and its applications. Enhancing the competitiveness of companies involved in UAV development and deployment.
7. Environmental Impact: Potential reduction in carbon footprint through the use of electric UAVs for various applications, contributing to sustainability goals.
The LUCAT project deals with designing, development and implementation of an integrated technology of spectrum cognizant communication and tracking system for low-altitude autonomous operations in densely populated areas for both manned and unmanned aerial vehicles (UAVs).
Key objectives of LUCAT is to develop advanced, robust and computationally efficient radar signal processing algorithms to detect and precisely track rapidly moving UAVs through a flight corridor that spans multiple radar sensors and spectrum-aware communication system. A major novelty of LUCAT is to cross-fertilize these two research areas (spectrum-cognizant communication and tracking system) towards mutual performance enhancements such that location can be used to improve performance metrics of communications, whereas communications may facilitate tracking UAVs operating at low altitudes.
The project idea consists of 4 major research domains: 1) precise detection and tracking of UAVs through radar; 2) classification of objects in the flight corridor; 3) 3D spectrum cartography for ground-air-ground channels; and 4) spectrum-cognizant ground-air-ground communications.
LUCAT will tackle the challenging requirements of the tracking and communication system for low-altitude corridors and provide 1) precise tracking of high speed UAVs and multiple UAVs; 2) very low latency, in the order of 15 milliseconds to match the fast dynamics of UAVs; 3) wide coverage and very high reliability, since the loss of communication may entail risks for security; 4) support for fast mobility, and 5) fast re-synchronization if the connection is lost. These are achieved by: 1) designing reduced complexity algorithms for detection and tracking, and 2) spectrum cognizant ground-air-ground communications.
