一种基于通信链路介入的专有空域无人机管控系统及方法
By using spectrum sensing and deep learning technologies, the radio frequency signals of drones are captured, and a multi-dimensional time-series feature vector sequence is constructed to achieve real-time intelligent analysis and stable takeover of unauthorized drone communication links. This solves the problem of rapidly handling drones in existing technologies and improves the reliability and security of identification and control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- LISHUI RES INST OF HANGZHOU UNIV OF ELECTRONIC SCI & TECH
- Filing Date
- 2026-05-13
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient to achieve real-time capture and parsing of unauthorized drone communication links, online modeling of protocol interaction sequences, dynamic positioning and stable control of key fields in a short period of time, making it difficult to achieve reliable control when rapidly handling drones in the airspace.
Radio frequency signals are captured by spectrum sensing devices, in-phase orthogonal components and signal entropy values are extracted, a multi-dimensional time-series feature vector sequence is constructed, unsupervised learning is performed using long short-term memory networks, protocol syntax trees are mined, a reinforcement learning agent is constructed to detect micro-perturbations, takeover control commands are generated, and the UAV is guided to land by combining a three-dimensional environmental potential field model.
It enables real-time intelligent analysis and stable takeover of unauthorized drone communication links, improves identification sensitivity and early warning capabilities, reduces the risk of false alarms and service interruption, and ensures the smoothness and security of the handling process.
Smart Images
Figure CN122176969B_ABST