C. Fruh, Mechanical Engineering Department, University of New Mexico / Air Force Research Laboratory, Space Vehicles) Directorate, NM, USA, M. Jah, (Air Force Research Laboratory, Space Vehicles Directorate, Albuquerque, NM), USA E. Valdez, (United States Geological Survey), Dept. of Biology, University of New Mexico, NM , P. Kervin, (Air Force Maui Optical & Supercomputing (AMOS), Kihei, HI, and T. Kelecy, (The Boeing Company, Colorado Springs, CO, Email: thomas.m.kelecy@boeing.com, Directorate, NM
Keywords: taxonomy, classification
Abstract:
As space gets more and more populated a classification scheme based upon scientific taxonomy is needed to properly identify and discriminate space objects. An artificial space object taxonomy also allows for scientific understanding of the nature of the space object population and the processes, natural or not, that drive changes of an artificial space object class from one to another. In general, parametric and non-parametric classification schemes based upon the developed taxonomy have to be distinguished. In both cases a priori information is needed either as training data or to outline error distributions as direct input values. In this paper a classification scheme based on the ancestral-dynamic state of space objects is proposed and linked to a cluster analysis of orbital element space without a priori clustering information is provided. The cluster analysis is based on a two step approach, a first using a cluster-feature tree and secondly, a minimal euclidian tree approach.
Date of Conference: September 10-13, 2013
Track: Orbital Debris