Date of Award:

5-2012

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Mechanical and Aerospace Engineering

Committee Chair(s)

David K. Geller

Committee

David K. Geller

Committee

R. Rees Fullmer

Committee

Stephen A. Whitmore

Abstract

An increasing number of missions require spacecraft to fly in close proximity. Despite the technological advances that have made these types of missions increasingly possible there remains a limit to how accurately the trajectory of a spacecraft can be predicted. As such, one of the main risks to spacecraft in close proximity is the threat of a collision. Many methods exist for computing the probability of collision between spacecraft. These methods incorporate the uncertainty in predicting the spacecrafts motion when computing an estimate. The accuracy and required computation time of these methods very greatly. A poor estimate of collision risk will not only increase the likelihood of a collision occurring, it can also carry other negative consequences. One possible side effect is additional fuel being spent to reduce the threat of a collision which is estimated to be high but in reality is low. This thesis explores several methods for estimating spacecraft collision probability and addresses wether each can be used effectively in real time while the spacecraft are on-orbit.

Each of the methods can be placed into one of three categories. The first category of methods do not directly estimate collision probability. Instead they place an upper limit on what the actual collision probability can be. The second category are methods which are capable of directly estimating collision probability over a time interval. The last category uses a common statistical analysis tool known as Monte Carlo to determine the probability of collision over an interval of time. This category also includes a novel method called Pseudo Monte Carlo. Each of the methods are compared and their accuracy are evaluated for a variety of orbit conditions.

Finally, an algorithm is proposed in which the methods are arranged in a hierarchy so that those methods which can be computed quickest are calculated first. As the proposed algorithm progresses the methods become more costly to compute, but yield more accurate estimates of collision probability. The result from each method is compared to a threshold value. If it exceeds the limits determined by mission constraints, the algorithm computes a more accurate estimate by utilizing the next method in the series. If the threshold is not reached, it is assumed there is a tolerable collision risk and the algorithm is terminated. In this way the algorithm is capable of adapting to the level of collision probability, and can be sufficiently accurate without needless calculations being performed. This work shows that collision probability can be systematically estimated.

Checksum

44d3cd85df3cc1cc78e7cedd58975d7b

Comments

This work made publicly available electronically on December 21, 2012.

Download

Share

COinS

Copyright for this work is retained by the student. If you have any questions regarding the inclusion of this work in the Digital Commons, please email us at .