A dynamic link attenuation prediction method and system based on a meteorological unmanned aerial vehicle and a buoy platform
By collecting meteorological parameters from the upper atmosphere and near the sea surface, and combining them with basic link parameters, the ARIMA model is used to predict dynamic link attenuation. This solves the problem of insufficient prediction of wireless communication links in marine environments in existing technologies, and enables stable and reliable communication between meteorological UAVs and buoy platforms.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- OCEANOGRAPHIC INSTR RES INST SHANDONG ACAD OF SCI
- Filing Date
- 2026-06-15
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, the wireless communication link prediction methods between meteorological drones and buoy platforms cannot effectively characterize the dynamic attenuation mechanism in the marine environment, resulting in a high risk of communication interruption or data loss. Existing models are not specific enough for marine scenarios, and the parameter settings are too idealistic or static, making it difficult to support the accurate planning and real-time optimization of highly reliable communication links.
By collecting meteorological parameters from the upper atmosphere and near the sea surface, and combining them with basic link parameters, we calculate free-space propagation loss and attenuation caused by various atmospheric factors. We then use the ARIMA prediction model to perform dynamic link attenuation prediction and early warning processing, collect meteorological parameters along the link transmission path in real time, and accurately calculate attenuation to provide data support for optimizing communication link parameters.
It enables dynamic and real-time prediction of the wireless communication link between meteorological drones and buoy platforms, ensuring communication stability and reliability under extreme weather conditions, and supporting marine meteorological monitoring, marine communication network optimization, and drone remote sensing data transmission.
Smart Images
Figure CN122419655A_ABST