Title:
Space Object Detection in Images Using Matched Filter Bank
and Bayesian Update
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 Issued
2015-12-11
Extent
Resource Type
Text
Resource Subtype
Masters Project
Rights Statement
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