Managing the risk of satellite collisions : a probabilistic risk analysis of improving space surveillance systems
Abstract/Contents
- Abstract
- Over the last several decades, the world has become increasingly reliant on the space domain. With the insertion of new spacecraft in various orbits, the risk of collisions with spacecraft or debris has increased. Currently, several space surveillance systems provide signals of such impending collisions and opportunities for owners and operators to respond to these alerts. The monitoring systems, however, are imperfect, and the current number of sensors of different types, costs, and levels of accuracy may need to be increased to allow better space traffic management. The objective of this dissertation is to estimate and optimize the benefits of such improvements. We present first, a general model to evaluate sensor systems based on a Bayesian updating of the prior probability of collision given two types of independent signals: some from more accurate but more expensive sensors, and some from less accurate but cheaper sensors. We use this model to evaluate the risks of collision of space assets given the current monitoring systems. We then assess the risk of losing a satellite constellation, which is where the satellites' values reside. Next, we assess the risk reduction value of adding one or more sensors of either type to the current monitoring systems, based on the classic notion of value of information. For simplicity, we assume a constant risk aversion in rational decisions, both for the sensor system managers and for the satellite operators. We illustrate the model by a fictionalized version of the United States Space Surveillance Network operated by the United States Air Force, and other sensor systems of lesser accuracy. Together, these networks collect optical and radar data, which allow synthesis of observations into a coherent picture of space. The results of this analysis can be used to support the selection of an optimal number of additional space surveillance sensors, either "large" or "small, " under resource constraints. This choice is sensitive to the risk aversion of both the users of the signals and the managers of the monitoring systems. The method can be extended to other types of monitoring system with similar structures.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Kim, Richard Hun | |
|---|---|---|
| Degree supervisor | Pate-Cornell, Elisabeth | |
| Thesis advisor | Pate-Cornell, Elisabeth | |
| Thesis advisor | Close, Sigrid | |
| Thesis advisor | Shachter, Ross | |
| Degree committee member | Close, Sigrid | |
| Degree committee member | Shachter, Ross | |
| Associated with | Stanford University, Department of Management Science and Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Richard Hun Kim. |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Richard Hun Kim
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...