Kelso, T.S., "A Look Back on Space Traffic Management (STM) from 2029," presented at the 20th Advanced Maui Optical and Space Surveillance Technologies Conference, Maui, HI, 2019 September 18.
Mahalo to the AMOS organizers for providing me this wonderful opportunity to share a look back from 2029 on how we developed what is now a successful and thriving STM environment. I am happy to be able to share my prepared remarks, as approved by the Time Council.
We’ve certainly come a long way.
- At the turn of the 21st century, people actually thought we didn’t need to worry about STM, because space was a big place.
- And satellite operators thought the only reason they had never received a conjunction warning was because of that, not because nobody was actually looking.
- Back then, nobody tried to do CA—other than DOD and then only for DOD satellites—because they believed it would take a supercomputer, millions of dollars, and couldn’t be done in a timely fashion. It didn’t.
- The community started by showing it could be done for all satellites in under an hour on a basic PC and then made it available via machine-to-machine interactions on the Internet.
- That was done using something called TLEs, which while good for their originally intended purpose of maintaining track custody, weren't suitable for CA (conjunction assessment).
- We realized that the hardest satellites to track—the operational ones that maneuvered regularly—had operators that were willing to share their ephemerides and maneuvers. That started in 2008 with pioneers like Intelsat, Inmarsat, SES, and Telesat, doing something that in 2019 might be called crowd sourcing.
- We realized that STM—unlike ATC—is not geographically limited and that any accidents would affect the global space commons. That meant STM was an international issue and an international organization was formed to manage data collection, quality control, analysis, and reporting.
- And satellite operators realized that STM was truly a collaborative effort and that individual operators or countries could not go it alone.
- Launch providers—on behalf of their launching states—began requiring proof of CA services as part of their launch certification process.
- Initially, we were constrained by trying to get better data, with commercial providers struggling to compete with SSA capabilities developed by DOD, because those were perceived to be “free.”
- In fact, they were not free, costing the US taxpayers billions of dollars each year.
- And US military organizations—anyone’s military organizations—could not provide the transparency required for CA, due to the nature of their missions.
- We found that commercial systems were much more agile in adopting new technology and mass-producing it to collect SSA that was accurate, persistent, and timely.
- And we recognized that commercial systems—even though much less expensive—needed to be paid for, too. We eventually did this via a global SSA co-op or marketplace, which allowed providers to focus on providing the best data possible.
- We realized the value of comparing results from diverse systems as part of an ongoing quality-control process to find inevitable problems in any system and this was greatly facilitated using artificial intelligence (AI).
- As satellites proliferated, operators realized the need to develop low-cost, passive tracking systems for all objects sent to space—including rocket bodies—to ensure tracking networks could quickly identify and track them under all conditions.
- As a community, we realized that leaving satellites and launch debris in orbit for 25 years (or longer) was irresponsible and adopted a more responsible pack-it-in/pack-it-out environmental perspective.
- We recognized that while distance was an easy-to-understand metric, that we needed to handle uncertainty and—more importantly—use risk in our decision making.
- We realized that probability of collision was not sufficient when comparing the chance of being hit by a 1-cm piece of debris or getting hit by an object the size of a school bus.
- We came to understand that accepting risk of minor collisions which might damage or even kill a single satellite was up to that satellite’s operator, but that standards for avoiding catastrophic collisions which would harm the space environment were an international decision.
- We worked to establish norms for generating/exchanging covariance data for orbits and maneuvers—even for launch.
- We realized that sharing data on location, size, and mass of satellites was no different than what we did to handle our driverless vehicles on the land, sea, and in the air and we worked together to collect that data.
- We changed the overall ops tempo of batch runs for CA to a continuous process of updating results as new data became available and quantum computing made that easy.
- We started openly sharing CA results with all operators in a collaborative fashion to ensure everyone had a common operating picture and could review all the quality-control data, as well.
- And AI and quantum computing made assessing collision avoidance maneuvers substantially easier than back in the early days.
- We mastered privacy, authentication, and data exchange standards to ensure this vital data was protected and users were confident as to its pedigree, using tools like blockchain.
- And concepts like what we used to call augmented reality, combined with machine learning that anticipated what an analyst wanted to see, made interacting with complex data systems intuitive and greatly facilitated helping decision makers understand their courses of action, especially in exceptional cases.
So, don't think because the ending will be good that there isn't a lot of work to be done today to get us there. That will take global collaboration and transparency and I’m confident that many of you in the audience today are prepared to work together and lead that effort!