Laboratory-scale demonstration of a Trajectory Control System for Balloons

A Trajectory Control System (TCS) for high-altitude scientific balloons has been a goal of the Balloon Program Office (BPO) for two decades. With the partial demonstration of a relative wind sensor last Fall (SPARROW-II), this goal is coming into focus despite the challenges which lay ahead. This project aims to advance towards the TCS goal by advancing the development of two distinct components: the Long Duration Balloon (LDB) anemometer and a laboratory-scale deployment demonstrator for the propeller. The anemometer prototype builds on the success of the SPARROW-II and -III flight success. The laboratory-scale deployment demonstrator seeks to demonstrate a successful deployment system capable of unfolding a 2-blade 5-ft radius propeller capable of operation at the low Reynolds number seen in the balloon environment.

First, a mature anemometer for high-altitude environments has the potential to aide in improving the forecasts of wind speeds in the lower stratosphere. Groups at GSFC has used flight data from Google Loon in the past to improve wind speed estimates (Coy, Schoeberl, Pawson, Candido, & Carver, 2019), which is a clear analog for what can be achieved from BPO’s many balloon missions each year should they fly anemometers. Second, the deployment system for large spinning structures can be used by other groups who have similar requirements for science conducted on large booms. Spinning structures perturb the angular momentum of the entire gondola, requiring some method for mitigating the rotational energy of the structure in a safe way. Finally, the final TCS concept will benefit balloon-borne science groups by increasing flight time while reducing the safety risk to the public (by avoiding cities and population centers). It is worth noting here that station keeping for NASA-sized balloons is prohibitive from a power perspective; yet it has been shown that biasing the trajectory of a balloon around a city is sufficient for prolonging flight (Yoder, 2022). This bias (or city avoidance) requires far less power and associated guidance system mass.

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