Space traffic pros need to know what the traffic looks like
By Moriba Jah|March 2022
A growing number of companies are ready to roll up their sleeves and take on the arduous task of cleaning and removing junk in orbital space. It brings a certain warmth to my heart to think of the industry looking after our near-Earth orbital ecosystem. However, there is a foundational level of knowledge about all space objects, including junk, that at present is in absentia in the civilian world and must be obtained and shared among all spacefaring nations and companies.
The world’s publicly available space object catalogs represent all objects as spheres, in essence, cannonballs. A spent rocket stage is modeled as a giant cannonball. The Landsat 9 imaging satellite is modeled as a large cannonball. A Starlink satellite is modeled as a small cannonball. A piece of satellite debris from Russia’s anti-satellite test last year is modeled as a tiny cannonball. Treating objects as though they are all the same shape is unique to the space domain. We regulate and model Vespa scooters differently than semitrucks, kayaks differently than oil tankers, and Boeing 777s differently than Cessna 152s.
Today’s approach is unsatisfactory, because nobody’s debris removal business model is predicated on removing cannonballs, but rather objects of irregular shapes with various material properties and tumbling at different speeds and orientations. Since no one can predict the size and shapes of the debris left by a collision, for instance, the physical traits of those objects are mostly unknown. Even for known satellites that have been dead on orbit for many years, the material aging effects on the satellite are also unknown. It would be a bad day for a space debris cleaning company to grab a dead satellite and have it shatter into hundreds or thousands of pieces because it was weak, fragile, or brittle. This lack of knowledge about a space object’s physical traits and structural integrity is at the heart of the on-orbit servicing and debris removal problem.
Another consequence of not knowing these physical traits is, inter alia, an inability to precisely predict orbital trajectories. Consider a nongravitational force acting on a satellite, such as the atmospheric drag that slows an object. Think of this sort of like sticking your hand out of a moving vehicle and feeling the air push your hand backward. If you change the orientation of your hand to the wind, you’ll feel more or less force pushing your hand backward. Well, by only representing the space object population as cannonballs, those of us in the orbit prediction business are strapped with a limit on how accurately and precisely we can predict where many of these objects will be in the future. A sphere has omnidirectional surfaces. A box consisting of flat sides, not so much. Not having a more realistic description of space objects makes it, at best, really difficult for a space debris removal company to acquire the information it needs to decide whether an object can be removed by its chosen technique.
The astronomy community also needs better trait characterization, both for reasons of pure science and to ensure humanity can detect dangerous asteroids and comets with adequate time to defend against them. Reflections off of human stuff are a nuisance at best for astronomers and at worst a dangerous impediment. Astronomers would benefit from a service for predicting the light pollution that their telescopes will experience during a hypothesized observation period or campaign. Cannonball models are insufficient for such a service, because space objects have complex shapes and reflective characteristics. A surface produces a glint, meaning a sudden flash of light, when its material properties have some level of specularity, or mirror-like reflection, and the direction perpendicular to this surface comes close to aligning with the phase angle bisector, which is the angle between the illumination source — in our case the sun — and the observer. When the phase angle bisector comes within a degree or so of perpendicular, the light is reflected directly to the observer as glint. Glints have been mistakenly confused as genuine astronomical phenomena, such as gamma ray bursts.
Sensing resources should be brought to bear on space object characterization to include developing and deploying (a) hypertemporal sensors that would measure the reflected photons at tens to hundreds of times per second and tell us something about the orientation and shape of the space object, and (b) multispectral sensors that would measure the reflected photons in different wavelengths, which tells us something about the material properties of the space object. Also, the United Nations Convention on Registration of Objects Launched into Outer Space should be updated to require adherents to describe the physical traits of all spacecraft launched from their territories, whether government or privately owned. My dream is to develop a participatory sensing network in which all would be invited to contribute information to a globally sourced space object database. Creating such a collaborative network is one goal of Privateer Space Inc., a company I co-founded last year with Steve Wozniak and Alex Fielding.
To be fair, measuring and inferring the physical traits of the near-Earth anthropogenic space object population will take years and a significant amount of dedicated funding and support. Moreover, there must be a database capable of ingesting, curating, and exposing these traits to the global community. None of this is even planned by the world’s leading space countries. Most scientific endeavors consider this task either beneath them or too applied to merit any consideration. And thus, this remains a core gap in our understanding of space debris. If we truly want to bring credible solutions to our space debris problem and space traffic management, we must develop a catalog that represents the space object population beyond the cannonball.
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