Team 3: Associating earth-orbiting objects detected by<br/><br/>astronomical telescopes

Wednesday, August 8, 2007 - 10:20am - 10:40am
EE/CS 3-180
Gary Green (The Aerospace Corporation)
Project description:
Astronomical telescopes detect the passage of an earth-orbiting
object as a streak in an image. Over a period of months, it is
possible that many objects will pass through the field of view,
some appearing more than once. There are estimates of 100,000
objects in orbit that might be detected by high resolution
telescopes. A large field of view telescope may see 100
streaks a night. Most of these objects are space debris that
pose a hazard to operational satellites. There is keen interest
within the space community to discover and track all these

If the telescope sensor is properly instrumented, it is
possible to obtain time-tagged pairs of angles that relate the
space object position to the sensor. With enough angle pairs,
it is possible to estimate the position and velocity (the
state) of the object, along with estimates of the uncertainties
of these parameters. The workshop problem is to develop
techniques to identify all the streaks made by each object.
Streaks created by an object must somehow be associated with
one another and disassociated from those made by other objects.
One solution approach treats the state data as vectors in R6
and uses statistical clustering techniques for the association.
A variation on this approach addresses physical properties of
the orbits, sorting according to those least likely to change
with small state variations.

Regardless of the approach, there are several interesting
aspects to the problem. Automatic streak detection is
required, with transform techniques of interest. Orbit
mechanics are essential to effective state estimation as well
as clustering techniques. In addition, traditional clustering
techniques are computationally taxing. A related problem is
identification of asteroids that might pose a hazard to planet


Vallado, David A., Fundamentals of Astrodynamics
and Applications, Edition 2, Microsoft Press, 2004; Milani,
Andrea, Three Short Lectures on Identifications and Orbit
2006; Kaufman, L. and Rousseeuw, P., Finding Groups in Data -
An Introduction to Cluster Analysis. Wiley Interscience 2005


computing proficiency demonstrated by knowledge of at least one
compiler, one semester differential equations, one semester

Desired: one
semester numerical analysis, familiarity with orbit mechanics
and estimation theory.

Keywords: orbit mechanics, astronomical telescopes,
statistical clustering

The Pan-starrs telescope on Mount Haleakela in Hawaii will be
used, among other tasks, to search for asteroids. However,
using its 1.4 billion pixel sensor, it will also detect
earth-orbiting objects.