A Real-Time Computational Model and Algoritm for Vision Based Detection and Tracking of Orbital Debris: NASA Technology Area 5.7 "Orbital Debris Tracking & Characterization"
Neda Nategh, Montana State University Awarded from 2015
Tracking and characterizing orbital debris– the “remains” of manmade objects orbiting the Earth– is critical to the safe and reliable operation of spacecraft in Earth orbit. The 2015 NASA Technology Roadmaps, which considers needed technologies and development pathways for the next 20 years, identifies needed technologies to measure and model orbital debris to maintain detailed knowledge of their characteristics in order to predict future collisions and potentially avoid them. As highlighted in the Technology Roadmaps, a critical gap is to track and characterize debris 10 to 100 times smaller than what is currently being tracked; and reduce tracking time to accommodate the larger number of targets being tracked.
This research project develops a robust, real-time computational model and algorithm to detect, segment and track moving objects in the presence of observer motion under difficult tasks in space motion tracking. This 1-year seed project will result in optimizing and validating the tracking algorithm recently developed in the PI’s lab for the performance goal of 2015 NASA Technology Area (TA) 5.7.1. This preliminary data will be used as a proof of concept to guide the system level design of a novel Orbital Debris Tracking Technology. This understanding will lay the foundation for subsequent research into vision based autonomous navigation, target recognition and tracking that are targeted at the needs of NASA applications, and will result in a research infrastructure enabling future research into space hardware implementation of the developed algorithms in collaboration with Space Science & Engineering Laboratory at Montana State University.
Electrical and Computer Engineering
Montana State University
Bozeman, MT 59717