UAS Architecture for Distributed Sensing Operations

NASA seeks Unmanned Aircraft Systems (UASs) for Earth science data collection for missions with variable durations, operating proximities, altitudes, and environmental conditions. Of particular interest is the Ice Bridge mission, which takes observations in support of Arctic and Antarctic research by identifying ice sheet motion, three-dimensional ice features, and other atmospheric and surface effects. These UAS aircraft may be equipped with a variety of sensors, with each aircraft potentially completing a unique set of objectives, only some of which take advantage of or require distributed sensing. Such a flexible system demands that vehicles be capable of seamless entry and exit of aircraft from any distributed sensing task. The approach proposed here satisfies these needs through a distributed sensing architecture that allows cluster sensor information to interface with and influence a multi-aircraft, high-precision, closed-loop path planning and control system. In addition, the UAS path planner is capable of managing dynamic flight regimes, including high winds and turbulence, while ensuring proper target tracking. This combination of features maximizes mission utility and path repeatability.

Distributed sensing for UASs has immediate significance for NASA's Ice Bridge project, which fills the gap between IceSat-1 and IceSat-2 for identifying ice sheet motion, three-dimensional ice features, and other atmospheric and surface effects. Characteristic measurements include some which require just one aircraft and others which will achieve significant improvements through distributed sensing. UAS sensing is important for other terrestrial science applications and has potential to support multiple aspects of the U.S. Global Change Research Program. These range from tracking severe weather events through the Genesis and Rapid Intensification Process (GRIP) program, which uses both manned and unmanned probes, to enabling aircraft-based interferometric synthetic aperature radar (InSAR) for tracking biomass distribution and ice sheet motion in anticipation of the Deformation, Ecosystem Structure and Dynamics of Ice (DESDyNI) spacecraft.

Non-NASA agencies can also realize benefits from both a distributed sensing architecture and robust path planning methodology for UASs. Such a system would enhance United States Geological Survey (USGS) vegetation assessments in low-accessibility swamplands and forests by reducing overall program costs and improving measurement fidelity through the use of multiple simultaneous sensors. The Civil Air Patrol and Coast Guard would both benefit from tracking applications similar to those proposed for Ice Bridge, which could be used to aid in ground or maritime search operations in inclement weather to both track and effectively locate emergency signals; this enhanced ability to find vessels in distress in otherwise dangerous weather would significantly improve survival rates by ensuring timely location of vessels in distress. As costs for UAVs decline, border patrol and state law enforcement could use this technology to track persons or goods through inaccessible or difficult locales without endangering ground personnel.

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