Using Hemispheric Sensing with Trajectory Prediction to Mechanically Dodge Space Debris

Team: 51

School: AIMS@UNM

Area of Science: Engineering

Interim: Problem
The current space environment is littered with thousands of “’all man-made objects including fragments and elements thereof, in Earth orbit or re-entering the atmosphere, that are non-functional’” (Klinkrad, 2010), collectively known as space debris. This no-longer purposeful debris now poses a threat to space vehicles still on missions in many sizes. Larger debris can be tracked from the ground, for sizes approximately 10 cm and larger (Garcia, 2017), and some programs like MASTER (a ground sensor-based system) can detect debris as small as 0.001 mm in diameter (Esa., 2018). However, many debris pieces less than 10 cm can begin to go untracked (Committee on Space Debris, 1995), but can still move at speeds that could present harm to a space vehicle still active (Garcia, 2017), like damaging windows on the space station (Cofield, 2017).
Most of this space debris comes from explosions and collisions (both deliberate and accidental), slag, and dust particles (Klinkrad, 2010). However, the space environment is predicted to only house more debris as cataloged objects begin to collide with each other and cause more fragmentations (Klinkrad, 2010). As this debris could damage expensive equipment, dodging it becomes more and more important as the density of space debris increases.
Some of the smaller debris that often go untracked are debris from surface degradation of spacecraft, such as paint flecks (Committee on Space Debris, 1995). However, exposed portions of spacecraft are still vulnerable to damage (Committee on Space Debris, 1995) from possible high velocity impacts (Garcia, 2017). Because the small debris are unable to be tracked by ground sensors and thus prohibit the arrangement for an orbital maneuver in advance, avoiding damage by collision would involve an onboard detection system.

Approach to Solve
In an attempt to work towards an onboard detection system for satellites, two aspects have been focused on: the sensors and the math. In order to have an onboard detection system that detects space debris, sensors are typically included. Sometimes hardware fails, so simulating the sensors may be a better approach to refine the processes before the hardware is more incorporated. In a more practical sense, a backup system that has more limited resources may be investigated. Also, research into the math behind the sensors is important, because it is one thing to be able to detect debris, but it is another to be able to calculate whether or not it is going to collide with the satellite. Therefore, researching and implementing math to go with the sensors is also an important aspect of the project.

So far, an attempt to characterize the current hardware sensors has been made. The hardware, however, has so far proved that it is not accurate enough for delicate measurements typically required for collision-predicting math, so an effort to virtually simulate the sensors is being investigated, especially for finding a backup system for a more complex setup. Also, a preliminary math algorithm has been used, but a more sophisticated potential solve is also being explored.

Expected Results
While results are not 100% predictable, some expected results include a more wholistic characterization of the physical sensors, a functional model that simulates the detection process, and adequate math to account for the most situations possible.

Cofield, C. (2017, December 10). Tiny Space-Debris Detector Will Fly to Station This Week. Retrieved August 26, 2019, from

Commission on Engineering and Technical Systems. (1995). Orbital debris: A technical assessment. Washington, D.C.: National Academies Press.

Esa. (2018, November 1). Analysis and prediction. Retrieved August 26, 2019, from

Garcia, M. (Eds.). (2017, August 7). Space Debris and Human Spacecraft. Retrieved August 28, 2019, from

Klinkrad, H. (2010 December 15). Space Debris. Wiley Online Library. doi: 10.1002/9780470686652.eae325

Team Members:

  McKenna Collins

Sponsoring Teacher: Creighton Edington

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