Hardware-in-the-Loop Comparison of Space Object Detection Tracking Methodologies
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Author(s)
Lee, Jared
Zubair, Lubna
Virani, Shahzad
Murphy, Timothy S.
Holzinger, Marcus J.
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Abstract
Space Domain Awareness relies on a network of surveillance architectures to catalog passive
and active space object data. This paper analyzes the performance of several detection
and tracking algorithms using different hardware-in-the-loop test configurations. Several image
sources are tested, including simulated images generated with the Hipparcos and Space
Object catalogs, and real images taken from a Nocturn XL camera. The Moving Target Indicator
(MTI), Multiple Hypothesis Tracking, and Finite Set Statistics algorithms are tested,
implemented, and compared in this study.
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Date
2016-02
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Text
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Paper
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