Date of Award

5-2018

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Aerospace, Physics, and Space Sciences

First Advisor

Csaba Palotai

Second Advisor

Gnana Bhaskar Tenali

Third Advisor

Daniel Batcheldor

Fourth Advisor

Eric Perlman

Abstract

The proper detection and analysis of bolide events ensures that we will once day be prepared for a big, catastrophic impact by a meteor. The data obtained from the analysis of these detected smaller events will provide important information about the meteor’s journey through our atmosphere and its orbit before it crossed the Earth’s path. SkySentinel is one of the All-Sky networks in charge of looking at the skies every night and detecting these objects as they fall. At the moment, SkySentinel’s detection process relies heavily on manpower to check whether their cameras picked up actual bolide events or false positives. The objective of the software outlined in this thesis is to develop a new, automated software to detect these events, which will eventually eliminate the need for that final, manual step. This software counts with more than a 80% success rate (on par with the best detection softwares) when it analyzes relatively short videos, marking a promising start to this new endeavor.

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