Strategic Enhancement of C-UAS through Advanced Human-Computer Collaborative Command and Control Mechanism

The command and control of unmanned aircraft systems (UASs) faces challenges such as multiple and heterogeneous sources of intelligence information, high operational agility requirements, complex and diverse threat patterns. The structures of traditional command information systems are difficult to effectively address these challenges, highlighting the urgency for innovative approaches. The efficacy of counter-UAS operations hinges upon the capability of combat systems to swiftly process intelligence, identify dynamic situational changes, and deploy operational resources in an accurate and efficient manner. However, traditional human-centric command paradigms fall short in meeting evolving demands, underscoring the necessity for new methodologies to address the escalating UAV threat.In response to these imperatives, this paper proposes an intelligent strategy model tailored for C-UAS command and control, emphasizing human-computer collaborative decision-making. Rooted in the OODA loop theory and informed by the characteristics of informatized, networked, and intelligent systems, this model aims to fulfill the imperatives of security, accuracy, and timeliness inherent in C-UAS. It designs a comprehensive framework structured around the counter operational process, dividing the task into four stages: multidimensional intelligence comprehensive situational awareness, spatiotemporal target locating, human-computer collaborative decision-making, and coordinated actions among equipment.This model provides a design framework based on the C-UAS application process, dividing the task into four stages. (1)Multidimensional intelligence comprehensive situation awareness. The fusion processing of multi-dimensional and multi-source information data forms a comprehensive and unified human-computer situational awareness capability. (2)Spatiotemporal target locating. Detection and identification of intelligence information to achieve accurate positioning and stable tracking of threat targets. (3)Human-computer collaborative decision-making. Division of labor and cooperation between humans and machines to improve decision-making efficiency, accuracy, and flexible adaptability. (4)Effectors coordinated actions. Rapid formation of a kill chain according to mission instructions, while possessing the ability to quickly switch kill chains.In order to verify the effectiveness of the proposed human-computer collaboration model, practical applications were conducted within an integrated C-UAS command and control system featuring diverse and heterogeneous equipment. The system was meticulously designed to address real-world operational exigencies through the implementation of cutting-edge methodologies, including multi-sensor autonomous collaboration, multi-target tracking optimization, and human-computer collaborative decision-making and evaluation. Field exercises were conducted in three typical operational scenarios: (1)Close-Range Surprise Raid of UAV assaults, (2)Drone Swarm Saturation Attacks from Multi-Direction, (3)Coordinated strikes by multiple UAVs. The system successfully detected and intercepted all incoming threats within the specified time, thereby demonstrating its autonomous operational capabilities in authentic battlefield environments.The outcomes of these experiments unequivocally affirm the capability of the human-computer collaborative system to detect suspicious targets, discern threat dynamics, assist commanders in decision-making, and orchestrate weapon systems for interception missions expediently and accurately. Moreover, the system demonstrates exceptional adaptability in swiftly responding to emergent threats and effectively engaging multiple targets from various directions.In conclusion, this research advocates an intelligent command and control strategy model underscored by human-computer collaboration, heralding a promising trajectory for enhancing the efficacy of C-UAS in modern warfare domains. By guiding the development and improvement of integrated C-UAS, this model is expected to strengthen defenses against the evolving UAV threat landscape while optimizing command efficiency in human-computer systems.