Development of model-embedded air data instrumentation and sensor integration for advanced unmanned aircraft

全球无人机市场增长非常迅速，推动了自动化、电池、材料和测量技术的发展。然而，技术似乎滞后的一个领域是空气数据收集：探测器和传感器的开发，这些传感器足够坚固，可以承受恶劣的操作和极端的环境，并且能够为飞行数据计算机提供速度、入射、侧滑和其他关键参数的测量。目前，无人机制造商必须在大型和重型飞机的皮托管系统和低质量和不可靠的低成本系统之间进行选择。因此，该项目的目的是开发无人机特有条件下使用空气数据传感器所需的模型和数据同化技术，并在耦合机身-传感器优化过程中使用这些模型来设计下一代分布式、机身集成的空气数据传感器。

The global market for UAVs has been growing very rapidly, driving forward technology in automation, batteries, materials and measurement. However, one area in which technology appears to be lagging is in air data gathering: the development of probes and sensors which are robust enough to survive rough handling and environmental extremes, and which are capable of providing measurements of velocity, incidence, sideslip, and other critical parameters to the flight data computer. UAV airframers must currently select between large and heavy aircraft Pitot systems and low-quality and unreliable low-cost systems for the hobby market. The purpose of this project, therefore, is to develop the models and data assimilation techniques required to use air data sensors for the specific conditions uniquely experienced by UAVs, and to use these models in a coupled airframe-sensor optimization process to design the next generation of distributed, airframe-integrated air data sensors.