22.4.2020

Black Swift Technologies Gets USAF Contract to Develop Tactical Weather Drone

Black Swift Technologies Gets USAF Contract to Develop Tactical Weather Drone – link

Source: UAS Vision

Article Headlines

  • Black Swift Technologies (BST) announced that it has been awarded a USAF SBIR Phase II contract to develop a UAS to autonomously conduct atmospheric profiling supporting more accurate cargo drops and improved localized weather forecasts supporting Air Force, Army and Special Operations Forces (SOF) operations
  • The aircraft, called the Black Swift SØ (S-zero), is a compact, yet rugged, aerial platform designed to be hand-launched and quickly climb up to 15,000 feet
  • Its unique tail design allows deep-stall landing with near vertical descent and 10-foot accuracy
  • The rapid ascent and descent allow the SØ to quickly and accurately capture 3-dimensional (3D) wind profiles at various levels—essential for precision cargo drops
  • Manufactured entirely in the USA, the SØ was engineered from inception for flight in extreme atmospheric conditions, including hurricane deployments, and has a 90-minute cruise time
  • The SØ is a cost-effective aerial solution perfect for determining the thermodynamics of the atmosphere. Its modular system design allows for rapid integration of new sensors and capabilities. The system’s onboard Multi-Hole Probe (MHP) measurements are tightly coupled with the aircraft’s control algorithms, allowing significant improvement in measurement accuracy, while its data formatting and transmission seamlessly integrate with existing Air Force systems

Overview & Comments

  • Mentioned in the article above, the SØ is planned to be hand launched thus if it will be required to conduct various measurements at larger ranges other means, such as aerial launched and maybe recovery, are required for physically getting the platform to the area of interest and recovery for minimizing the potential for exposure
  • The further away the special operations / cargo drops will be conducted the more accurate the data needs to be in order to minimize unknowns
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