Research & Innovation

Passing Interference: Helping Astronomers and Satellites Coexist

Supported by NSF, a Stevens research duo will develop hardware and algorithms to cut down on the radio interference produced by thousands of newly launched satellites

For years, radio astronomy has revealed astonishing insight after insight about our universe.

Radio astronomers peer at distant objects using high-tech radio telescopes and processing software to see things that can’t be seen with optical telescopes alone. These special telescopes observe celestial objects and phenomena using radio frequency (RF) waves, which can pass through dust clouds and other objects that might block or absorb light — revealing what’s behind or beyond.

But now there’s a problem: the exploding satellite traffic from companies like SpaceX creates significant radio interference (RFI) that clouds the signals and images radio telescopes and other instruments are continuously collecting.

“RFI can obscure faint astronomical objects, create false signals, reduce the sensitivity of radio telescopes and lead to significant loss of data and bandwidth limitation,” explains Stevens professor Hongbin Li, a leading expert in RF sensing.

In an effort to help radio astronomers see more clearly, Li is now working with fellow Stevens researcher and satellite expert Rod Kim on a National Science Foundation (NSF)-supported project to devise ways to help the two fields — satellites and astronomy — coexist.

Fold-wrapping signals for freshness

Satellite traffic in the skies has absolutely exploded in recent years.

Twenty years ago, the planet was orbited by fewer than a thousand satellites; today, there are more than 11,000 circling overhead, with more on the way. SpaceX’s Starlink service alone represents up to half of that number, and the company has publicly stated intentions of eventually launching as many as 100,000 satellites into low-earth orbits for various business purposes within the foreseeable future.

About two thousand new satellites are launched worldwide each year, each throwing off large quantities of radio signals and RFI — bad news for radio astronomers and their land-based signal receivers.

The NSF foresaw this problem coming. In 2022 It created SWIFT (Spectrum and Wireless Innovation enabled by Future Technologies), a funding program focused on effective radio-spectrum utilization and coexistence — particularly by using so-called passive techniques, which involve situations where one of the parties (in this case, the astronomy) doesn’t produce interference but it significantly affected by it.

Earlier this year, Li and Kim secured a $700,000 award from SWIFT’s sub-program SWIFT-SAT to work intensively on this rapidly growing challenge.

“RFI isn’t going away,” notes Kim. “That’s a fact of life. Radio astronomers will need to cope with this issue, one way or another, for years and decades going forward.”

The pair plan to attack the problem on both the hardware and the software fronts, designing novel circuits as well as new algorithmic processing methods that will work to cut out as much of the overlapping interference as possible.

Potential hardware innovations could include newly designed, stronger radio receivers that can tolerate higher-power inputs across wider spectra, as well as higher-dynamic digital ranges. That would mean new circuitry designed by hand on the bench in Stevens labs by faculty and students.

On the software side, Li and Kim will work to improve interferometric imaging techniques, which collect and process multiple overlapping views and data from the sky to create accurate images. One technique they’re especially excited about pursuing is known as “modulo sampling.”

While complex, the modulo technique essentially boils down to electronically wrapping and folding received radio signals — using specialized proprietary algorithms rather than any sort of physical process — into a more usable, cleaner form.

“This algorithmic wrapping preserves and converts the weak astronomical signals into a more compact form that can still be readily processed,” explains Li, “while still retaining accuracy even in the presence of strong interference.”

The two researchers’ hope is that the process will retain the very best data from the RF signals as images are created from them, avoiding the cloudy and corrupting effects of RFI that might ruin clear pictures.

The project will continue through at least 2027.