IDA Ideas

Orbital Debris and Kinetic Anti-satellite Concerns: How a “Kessler Syndrome” Threatens U.S. Use of Space Assets

IDA Ideas host Rhett Moeller spoke to IDA President Norton Schwartz, Joel Williamsen of the IDA Systems and Analyses Center’s Operational Evaluation Division, and James Heagy of the IDA Systems and Analyses Center’s Science and Technology Division about the threat of orbital debris and kinetic anti-satellite (ASAT) weapons to the economic and military value of satellites in low Earth orbit (LEO), especially satellite constellations. Many of the comments in this podcast arose during the IDA Forum on Orbital Debris Risks and Challenges, held on October 8–9, 2020, and attended by IDA researchers and decision makers from the Department of Defense (DoD), U.S. Air Force, Department of Commerce, NASA, Federal Aviation Administration, and Federal Communications Commission.

IDA has supported nearly 20 years of sponsored and independent research into the effects of orbital debris and ASAT weapons on satellite systems. This research has intensified in recent years due to the phenomenal growth in satellite constellations in LEO, and the DoD’s expected use of such constellations for national defense. Much of IDA’s work has centered on predicting the effect of orbital debris on spacecraft mission loss, both in the short term from collateral damage due to satellite collisions or ASAT tests and in the long term as the background orbital debris population continues to grow. This growth has led to what many researchers believe to be the beginning stages of a Kessler Syndrome, named after the original NASA researcher who predicted the onset of a self-sustaining debris growth environment as existing debris hits operating and nonoperating satellites, creating more debris. Such a debris environment increases the risk of losing reliable and safe access to affected regions of space.

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Weaponized Tweets: Artificial Intelligence to Defend Against Influence Operations in Social Media

IDA Ideas host Rhett Moeller spoke to researchers from the Science and Technology Division of IDA’s Systems and Analyses Center about their use of machine learning to create a prototype system for analyzing Twitter posts that U.S. adversaries made to influence public opinion in the years leading up to the 2016 U.S. Presidential election. Joining him are Shelley Cazares, who leads the ongoing project, and two members of her team, Emily Parrish and Jenny Holzer.

The project began in 2018 with about three million tweets from early 2012 through early 2018 that had been posted by the Russian-backed Internet Research Agency. The team set out to create a prototype system using open-source software tools that could have helped intelligence analysts during that time. Using a machine learning technique called Latent Dirichlet Allocation and open-source software called MALLET, the team found that the topics of the adversary’s tweets evolved over time into several tactical phases. Specifically, their English tweet topics grew tighter over time, more specific, more negative, and more polarizing, with their final pattern solidifying one full year before the 2016 election. With this system, this and other revealing information about U.S. adversaries’ social media operations could be reported to U.S. Government decision makers with as little as one month of lag time.

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China's Commercial Space Sector

In this episode of IDA Ideas, host Rhett Moeller interviews researchers from IDA’s Science and Technology Policy Institute (STPI) about their research into China’s commercial space sector. STPI researchers Bhavya Lal, Irina Liu, Shirley Han, and Tom Colvin provide an overview of their work, their discussions with Chinese space experts, their thoughts on technological advancements in China, and their assessment of China’s strengths and weaknesses in the sector.

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