GNSS Simulator to Achieve Immersive Drone Testing

Abstract

Today, traditional drone testing techniques are of poor quality. Drones are either tested outdoors quite remote from the oWeather, winds, thermals, and turbulence pose an ever-present challenge to small Unmanned Aerial Systems (UAS). These challenges become magnified in rough terrain and especially within urban canyons. As the industry moves to Beyond Visual Line of Sight (BVLOS) operations, resilience to weather perturbations will be key. As the human decision-maker is removed both from the in-situ environment and from one-to-one responsibility for the safety of the air vehicles under his or her control, better weather detection and prediction at increasingly small scales becomes vital to preserving the safety of the National Airspace System (NAS).

In order to provide decision-quality weather information to the UAS pilot or operator, two critical pieces of the puzzle are required. First, better detection and prediction capabilities at a much smaller scale are required. However, prediciton cannot account for local, dynamic perturbations. The pilot or operator need to understand the effects of weather on the specific UAS for which they are responsible. This area of knowledge – the effect of the disturbance on a UAS and its ability to reject this disturbance - presents some unique concerns, especially for commercial UAS which tend to be designed with Commercial Off the Shelf (COTS) components, and have rapid development, deployment, and disposal cycles.

Second, understanding the influence weather has on small UAS is imperative as we start to define the performance requirements for the Unmanned Traffic Management (UTM) system. Indeed, the UTM concept is based on the idea that users of the system will share their intent amongst themselves and thus achieve a type of strategic deconfliction. As the size of the operational volumes reserved shrinks, the flight plan looks more and more like a four-dimensional trajectory ( 4DT) operation. Multiple vehicle 4DT requires a sufficiently "tight" – or at least quantified – performance from the UAS to guarantee safety. In fact, the current standard for UTM requires that the UAS shared intend or “flight plan” include enough buffer to contain the UAS 95% of the time.

This paper presents the work done to date in developing a repeatable technique for quanti- fying the response to disturbances and the associated ability to maintain course and timeline (i.e. 4DT “flight plan”) of a commercially relevant, operationally representative UAS.

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