Jessica T. Anderson, David E. Gaylor, Dunning Idle 5th, (Emergent Space Technologies, Inc.), Ryan P. Russell, Ashley Biria, Maximilian Schadegg, (The University of Texas at Austin)
https://doi.org/10.64861/FXIX8551
Keywords: RSO Feature Identification
Abstract:
As the number of objects in orbit and spacecraft capability grows, the need for space situational awareness (SSA) also increases. The identification and cataloging of resident space objects (RSOs) is a large and complex problem, and new methods of performing these tasks are necessary to keep up with the rapid growth of objects in space. Emergent Space Technologies, Inc. (Emergent) and the University of Texas at Austin (UT) worked together to develop an algorithm to aid in detecting RSO characteristics using a Hierarchical Mixture of Experts (HME). This algorithm has been tested in simulation, and has been shown to be capable of detecting the size, shape, reflectivity, and maneuvers performed by an RSO.
Date of Conference: September 10-13, 2013
Track: Non-Resolved Object Characterization’