An Innovative Unmanned Aircraft System Design for Optimal Temperature, Humidity, Wind Speed, and Direction Measurements

The measurement of temperature, humidity and wind is one of the most important parameters for the description of the thermodynamic and kinematic structure of the planetary boundary layer. There are currently several meteorological instruments able to measure these parameters effectively, however, limited in coverage and with high operation costs.

The Unmanned Aircraft Systems (UAS) is an emerging technology with a growing interest for weather research and atmospheric monitoring. Correspondingly, we are witnessing rapid developments in autopilot capabilities, control software, and airframes themselves. However, a design that completely satisfies the requirements of measuring the atmosphere accurately is still a challenge. In this presentation, we focus on designing a system capable of collecting accurate and uncontaminated atmospheric data from UAS. As is known in physics, the observer effect theory states that by simply observing a phenomenon, its properties changes. This is mostly seen on instruments that, by necessity, alter the state of what they measure in some manner. Therefore, in order to minimize the observer effect, an optimal sensor-UAS integration design must be achieved to keep the sensors away from undesired heat sources and prevent any contamination coming directly from the UAS body. To address this challenge, we have created digital models of the UAS body and subjected them to flow simulations using CAD software. After several design iterations, the results are a more streamline design as well as the proof that the sensors are getting a clean air flow across them for a large range of flight patterns and wind conditions. The UAS body design was also drastically simplified by adding a custom wind tracker function in the autopilot code that allows the UAS to turn such that it always faces into the wind.

In this presentation, a brief overview of the hardware and software components being used for fight control, data acquisition and processing, and communication, both between the UAV and the ground station and the ground station and the Internet is given. We then provide examples of how these elements can be integrated into UAS to provide adaptive atmospheric sampling strategies, which are relatively platform and sensor agnostic.

The Center for Autonomous Sensing and Sampling (CASS) team is constantly making efforts to further improve upon and integrate atmospheric sensors that effectively exploit the UAS advances in order to close the gap between the state of the art UAS engineering and meteorological research.