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IRIDE pathfinder satellite has launched
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By European Space Agency
The second of the Meteosat Third Generation (MTG) satellites and the first instrument for the Copernicus Sentinel-4 mission are fully integrated and, having completed their functional and environmental tests, they are now ready to embark on their journey to the US for launch this summer.
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By NASA
5 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Jeremy Frank, left, and Caleb Adams, right, discuss software developed by NASA’s Distributed Spacecraft Autonomy project. The software runs on spacecraft computers, currently housed on a test rack at NASA’s Ames Research Center in California’s Silicon Valley, and depicts a spacecraft swarm virtually flying in lunar orbit to provide autonomous position navigation and timing services at the Moon. NASA/Brandon Torres Navarrete Talk amongst yourselves, get on the same page, and work together to get the job done! This “pep talk” roughly describes how new NASA technology works within satellite swarms. This technology, called Distributed Spacecraft Autonomy (DSA), allows individual spacecraft to make independent decisions while collaborating with each other to achieve common goals – all without human input.
NASA researchers have achieved multiple firsts in tests of such swarm technology as part of the agency’s DSA project. Managed at NASA’s Ames Research Center in California’s Silicon Valley, the DSA project develops software tools critical for future autonomous, distributed, and intelligent swarms that will need to interact with each other to achieve complex mission objectives.
“The Distributed Spacecraft Autonomy technology is very unique,” said Caleb Adams, DSA project manager at NASA Ames. “The software provides the satellite swarm with the science objective and the ‘smarts’ to get it done.”
What Are Distributed Space Missions?
Distributed space missions rely on interactions between multiple spacecraft to achieve mission goals. Such missions can deliver better data to researchers and ensure continuous availability of critical spacecraft systems.
Typically, spacecraft in swarms are individually commanded and controlled by mission operators on the ground. As the number of spacecraft and the complexity of their tasks increase to meet new constellation mission designs, “hands-on” management of individual spacecraft becomes unfeasible.
Distributing autonomy across a group of interacting spacecraft allows for all spacecraft in a swarm to make decisions and is resistant to individual spacecraft failures.
The DSA team advanced swarm technology through two main efforts: the development of software for small spacecraft that was demonstrated in space during NASA’s Starling mission, which involved four CubeSat satellites operating as a swarm to test autonomous collaboration and operation with minimal human operation, and a scalability study of a simulated spacecraft swarm in a virtual lunar orbit.
Experimenting With DSA in Low Earth Orbit
The team gave Starling a challenging job: a fast-paced study of Earth’s ionosphere – where Earth’s atmosphere meets space – to show the swarm’s ability to collaborate and optimize science observations. The swarm decided what science to do on their own with no pre-programmed science observations from ground operators.
“We did not tell the spacecraft how to do their science,” said Adams. “The DSA team figured out what science Starling did only after the experiment was completed. That has never been done before and it’s very exciting!”
The accomplishments of DSA onboard Starling include the first fully distributed autonomous operation of multiple spacecraft, the first use of space-to-space communications to autonomously share status information between multiple spacecraft, the first demonstration of fully distributed reactive operations onboard multiple spacecraft, the first use of a general-purpose automated reasoning system onboard a spacecraft, and the first use of fully distributed automated planning onboard multiple spacecraft.
During the demonstration, which took place between August 2023 and May 2024, Starling’s swarm of spacecraft received GPS signals that pass through the ionosphere and reveal interesting – often fleeting – features for the swarm to focus on. Because the spacecraft constantly change position relative to each other, the GPS satellites, and the ionospheric environment, they needed to exchange information rapidly to stay on task.
Each Starling satellite analyzed and acted on its best results individually. When new information reached each spacecraft, new observation and action plans were analyzed, continuously enabling the swarm to adapt quickly to changing situations.
“Reaching the project goal of demonstrating the first fully autonomous distributed space mission was made possible by the DSA team’s development of distributed autonomy software that allowed the spacecraft to work together seamlessly,” Adams continued.
Caleb Adams, Distributed Spacecraft Autonomy project manager, monitors testing alongside the test racks containing 100 spacecraft computers at NASA’s Ames Research Center in California’s Silicon Valley. The DSA project develops and demonstrates software to enhance multi-spacecraft mission adaptability, efficiently allocate tasks between spacecraft using ad-hoc networking, and enable human-swarm commanding of distributed space missions. NASA/Brandon Torres Navarrete Scaling Up Swarms in Virtual Lunar Orbit
The DSA ground-based scalability study was a simulation that placed virtual small spacecraft and rack-mounted small spacecraft flight computers in virtual lunar orbit. This simulation was designed to test the swarm’s ability to provide position, navigation, and timing services at the Moon. Similar to what the GPS system does on Earth, this technology could equip missions to the Moon with affordable navigation capabilities, and could one day help pinpoint the location of objects or astronauts on the lunar surface.
The DSA lunar Position, Navigation, and Timing study demonstrated scalability of the swarm in a simulated environment. Over a two-year period, the team ran close to one hundred tests of more complex coordination between multiple spacecraft computers in both low- and high-altitude lunar orbit and showed that a swarm of up to 60 spacecraft is feasible.
The team is further developing DSA’s capabilities to allow mission operators to interact with even larger swarms – hundreds of spacecraft – as a single entity.
Distributed Spacecraft Autonomy’s accomplishments mark a significant milestone in advancing autonomous distributed space systems that will make new types of science and exploration possible.
NASA Ames leads the Distributed Spacecraft Autonomy and Starling projects. NASA’s Game Changing Development program within the agency’s Space Technology Mission Directorate provides funding for the DSA experiment. NASA’s Small Spacecraft Technology program within the Space Technology Mission Directorate funds and manages the Starling mission and the DSA project.
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Last Updated Feb 04, 2025 Related Terms
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By European Space Agency
Hisdesat, Spain's premier provider of secure satellite communications, is set to launch its SpainSat Next Generation I (SNG I) satellite aboard a SpaceX Falcon 9 rocket on 29 January from Cape Canaveral, Florida at 20:34 EST (30 January at 02:34 CET). The European Space Agency (ESA)-supported satellite will provide more cost-effective, adaptable and secure communication services for governments and emergency response teams across Europe, North and South America, Africa, the Middle East and up to Singapore in Asia.
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By NASA
NASA’s Jet Propulsion Laboratory used radar data taken by ESA’s Sentinel-1A satellite before and after the 2015 eruption of the Calbuco volcano in Chile to create this inter-ferogram showing land deformation. The color bands west of the volcano indicate land sinking. NISAR will produce similar images.ESA/NASA/JPL-Caltech A SAR image — like ones NISAR will produce — shows land cover on Mount Okmok on Alaska’s Umnak Island . Created with data taken in August 2011 by NASA’s UAVSAR instrument, it is an example of polarimetry, which measures return waves’ orientation relative to that of transmitted signals.NASA/JPL-Caltech Data from NASA’s Magellan spacecraft, which launched in 1989, was used to create this image of Crater Isabella, a 108-mile-wide (175-kilometer-wide) impact crater on Venus’ surface. NISAR will use the same basic SAR principles to measure properties and characteristics of Earth’s solid surfaces.NASA/JPL-Caltech Set to launch within a few months, NISAR will use a technique called synthetic aperture radar to produce incredibly detailed maps of surface change on our planet.
When NASA and the Indian Space Research Organization’s (ISRO) new Earth satellite NISAR (NASA-ISRO Synthetic Aperture Radar) launches in coming months, it will capture images of Earth’s surface so detailed they will show how much small plots of land and ice are moving, down to fractions of an inch. Imaging nearly all of Earth’s solid surfaces twice every 12 days, it will see the flex of Earth’s crust before and after natural disasters such as earthquakes; it will monitor the motion of glaciers and ice sheets; and it will track ecosystem changes, including forest growth and deforestation.
The mission’s extraordinary capabilities come from the technique noted in its name: synthetic aperture radar, or SAR. Pioneered by NASA for use in space, SAR combines multiple measurements, taken as a radar flies overhead, to sharpen the scene below. It works like conventional radar, which uses microwaves to detect distant surfaces and objects, but steps up the data processing to reveal properties and characteristics at high resolution.
To get such detail without SAR, radar satellites would need antennas too enormous to launch, much less operate. At 39 feet (12 meters) wide when deployed, NISAR’s radar antenna reflector is as wide as a city bus is long. Yet it would have to be 12 miles (19 kilometers) in diameter for the mission’s L-band instrument, using traditional radar techniques, to image pixels of Earth down to 30 feet (10 meters) across.
Synthetic aperture radar “allows us to refine things very accurately,” said Charles Elachi, who led NASA spaceborne SAR missions before serving as director of NASA’s Jet Propulsion Laboratory in Southern California from 2001 to 2016. “The NISAR mission will open a whole new realm to learn about our planet as a dynamic system.”
Data from NASA’s Magellan spacecraft, which launched in 1989, was used to create this image of Crater Isabella, a 108-mile-wide (175-kilometer-wide) impact crater on Venus’ surface. NISAR will use the same basic SAR principles to measure properties and characteristics of Earth’s solid surfaces.NASA/JPL-Caltech How SAR Works
Elachi arrived at JPL in 1971 after graduating from Caltech, joining a group of engineers developing a radar to study Venus’ surface. Then, as now, radar’s allure was simple: It could collect measurements day and night and see through clouds. The team’s work led to the Magellan mission to Venus in 1989 and several NASA space shuttle radar missions.
An orbiting radar operates on the same principles as one tracking planes at an airport. The spaceborne antenna emits microwave pulses toward Earth. When the pulses hit something — a volcanic cone, for example — they scatter. The antenna receives those signals that echo back to the instrument, which measures their strength, change in frequency, how long they took to return, and if they bounced off of multiple surfaces, such as buildings.
This information can help detect the presence of an object or surface, its distance away, and its speed, but the resolution is too low to generate a clear picture. First conceived at Goodyear Aircraft Corp. in 1952, SAR addresses that issue.
“It’s a technique to create high-resolution images from a low-resolution system,” said Paul Rosen, NISAR’s project scientist at JPL.
As the radar travels, its antenna continuously transmits microwaves and receives echoes from the surface. Because the instrument is moving relative to Earth, there are slight changes in frequency in the return signals. Called the Doppler shift, it’s the same effect that causes a siren’s pitch to rise as a fire engine approaches then fall as it departs.
Computer processing of those signals is like a camera lens redirecting and focusing light to produce a sharp photograph. With SAR, the spacecraft’s path forms the “lens,” and the processing adjusts for the Doppler shifts, allowing the echoes to be aggregated into a single, focused image.
Using SAR
One type of SAR-based visualization is an interferogram, a composite of two images taken at separate times that reveals the differences by measuring the change in the delay of echoes. Though they may look like modern art to the untrained eye, the multicolor concentric bands of interferograms show how far land surfaces have moved: The closer the bands, the greater the motion. Seismologists use these visualizations to measure land deformation from earthquakes.
Another type of SAR analysis, called polarimetry, measures the vertical or horizontal orientation of return waves relative to that of transmitted signals. Waves bouncing off linear structures like buildings tend to return in the same orientation, while those bouncing off irregular features, like tree canopies, return in another orientation. By mapping the differences and the strength of the return signals, researchers can identify an area’s land cover, which is useful for studying deforestation and flooding.
Such analyses are examples of ways NISAR will help researchers better understand processes that affect billions of lives.
“This mission packs in a wide range of science toward a common goal of studying our changing planet and the impacts of natural hazards,” said Deepak Putrevu, co-lead of the ISRO science team at the Space Applications Centre in Ahmedabad, India.
Learn more about NISAR at:
https://nisar.jpl.nasa.gov
News Media Contacts
Andrew Wang / Jane J. Lee
Jet Propulsion Laboratory, Pasadena, Calif.
626-379-6874 / 818-354-0307
andrew.wang@jpl.nasa.gov / jane.j.lee@jpl.nasa.gov
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Last Updated Jan 21, 2025 Related Terms
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