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3D Airspace analysis using the CloudRF API

Tutorial on performing 3D Airspace analysis using the CloudRF API. A RADAR or C-UAS system will have blind spots from terrain and buildings which must be simulated to visualise the true coverage or to identify a better site. Two scenarios are demonstrated using the free python script linked below: Air surveillance Radar (100km): This template uses the GPU accelerated Radar propagation model with a 100m radar cross section (RCS) and digital terrain to show the coverage up to 10,000ft above sea level. Counter Drone system (2km): This template uses the GPU accelerated ITU_R P.1812 / TSB-88 propagation model with high resolution LiDAR data to show drone height up to 120m above ground level. The python script used generates Area API calls to either CloudRF or a private SOOTHSAYER server which it downloads as GeoTIFF rasters. These rasters are analysed to extract the edges to KML polygon files. The KML files are compatible with ATAK, WINTAK, TAKX and Google Earth. Python script: https://github.com/Cloud-RF/CloudRF-A... API: https://cloudrf.com/documentation/dev...