Space Object Detection in Images Using Matched Filter Bank
and Bayesian Update
Author(s)
Murphy, Timothy S.
Advisor(s)
Holzinger, Marcus J.
Editor(s)
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Abstract
Electro-optical sensors, when used to track space objects, are often used to produce detections for some orbit
determination scheme. Instead, this paper proposes a series of methods to use electro-optical images directly in
orbit determination. This work uses the SNR optimal image filter, called a matched filter, to search for partially
known space objects. By defining a metric for measuring matched filter template similarity, a bank of matched
filters is efficiently defined by partitioning the prior knowledge set. Once partitioned sets are known, the matched
filter bank can be localized to regions of the sky. A method for hypothesis testing the result of a matched filter
for a space object is developed. Finally, a framework for orbit determination based on the matched filter result is
developed. Simulation shows that the analytic results enable a better framework for implementing matched filters
for low SNR object detection
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Date
2015-12-11
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Resource Type
Text
Resource Subtype
Masters Project
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