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SwRI, international team use deep learning to create virtual 'super instrument'
by Staff Writers
San Antonio TX (SPX) Oct 08, 2019

The virtual super instrument is already in use as part of a Frontier Development Laboratory project for forecasting ionospheric disturbances. Munoz-Jaramillo is currently working on additional super instruments that combine other capabilities. See video presentation here

A study co-written by a Southwest Research Institute scientist describes a new algorithm that combines the capabilities of two spacecraft instruments, which could result in lower cost and higher efficiency space missions. The virtual "super instrument," is a computer algorithm that utilizes deep learning to analyze ultraviolet images of the Sun, taken by NASA's Solar Dynamics Observatory, and measure the energy that the Sun emits as ultraviolet light.

"Deep learning is an emerging capability that is revolutionizing the way we interact with data," said Dr. Andres Munoz-Jaramillo, senior research scientist at SwRI. Munoz-Jaramillo co-authored the study, published this month in Science Advances, alongside collaborators from nine other institutions as part of NASA's Frontier Development Laboratory.

The laboratory is an applied artificial intelligence research accelerator that applies deep learning and machine learning techniques to challenges in space science and exploration.

Deep learning is a type of machine learning methods that mimic the way the human brain processes information. The result of deep learning is machines accomplishing things that previously required human intelligence, such as translation between foreign languages, driving a vehicle and facial recognition.

Things like Netflix suggesting what to watch next, an iPhone unlocking upon sight of its owner's face and Alexa responding to a vocal request are all results of deep learning.

"All missions beyond Earth have a host of instruments that have been designed with specific capabilities to answer specific scientific questions," Munoz-Jaramillo said. "When we combine them into virtual super instruments, we can produce more cost-effective missions with higher scientific impact or use measurements by one instrument to help answer the science questions of another."

Munoz-Jaramillo stresses in the study that these virtual super instruments will not make hardware obsolete. They will always require a spacecraft to collect the necessary data for virtualization.

"Deep learning instruments cannot make something out of nothing, but they can significantly enhance the capabilities of existing technology," he said.

Their virtual super instrument is already in use as part of a Frontier Development Laboratory project for forecasting ionospheric disturbances. Munoz-Jaramillo is currently working on additional super instruments that combine other capabilities.

"In essence, deep learning involves sophisticated transformation of data," he said. "We can make these transformations into scientifically useful data and modernize the way we view not just the Sun, but a great number of scientific questions."

Research paper

Related Links
Heliophysics at SWRI
Space Technology News - Applications and Research

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ESA selects AdaCore's qualified multitasking solution for spacecraft software development
Newport UK (SPX) Sep 27, 2019
AdaCore reports that the European Space Agency (ESA) has selected AdaCore to provide a qualified multitasking solution for spacecraft software development to support multiple ongoing and future ESA projects. As part of this contract, AdaCore has implemented a pre-qualified version of the Ravenscar Small Footprint (SFP) library - a configurable Ada run-time library that implements the Ravenscar profile, allows customisation for specific platforms and capabilities, and is suitable for qualification ... read more

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