Measuring the Return on Investment and Real Option Value of Weather Sensor Bundles for Air Force Unmanned Aerial Vehicles
Abstract
Weather-related losses of remotely piloted aircraft (RPA) have exceeded $100 million over the past 20 years (Preisser and Stutzreim, 2015). The growing ubiquity of RPAs in routine combat operations is driving fundamental changes to the nature of support for these unmanned aircraft. Support requirements such as bandwidth availability, data transmission capabilities, digital interoperability, and weather forecasting are being pushed to unprecedented limits to ensure they enhance RPA performance without imposing superfluous constraints. A persistent trend plaguing RPA operators has been poor environmental situational awareness degrading overall operational effectiveness. The impact of suboptimal weather forecasting, especially regarding adverse weather conditions, on RPAs is significant, and it is driving an increasing need for fundamental changes to a system that has matured over several decades of proven operational success with manned aircraft. Without humans in the cockpit, the nature and frequency of weather forecasting processes and supporting technologies must evolve to enable optimized RPA operational performance by providing weather products that achieve high levels of resolution, accuracy, and timeliness.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 30, 2016
- Accession Number
- AD1016692
Entities
People
- Dave Harris
- David Ford
- Johnathan C. Mun
- Matt Cornachio
- Sandra Hom
- Thomas Housel
Organizations
- Naval Postgraduate School