Uncued Low SNR Detection with Likelihood from Image Multi Bernoulli Filter
Author(s)
Murphy, Timothy S.
Holzinger, Marcus J.
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Abstract
Both SSA and SDA necessitate uncued, partially informed detection and orbit determination efforts
for small space objects which often produce only low strength electro-optical signatures. General
frame to frame detection and tracking of objects includes methods such as moving target indicator,
multiple hypothesis testing, direct track-before-detect methods, and random finite set based multi-object
tracking. This paper will apply the multi-Bernoulli filter to low signal-to-noise ratio (SNR),
uncued detection of space objects for space domain awareness applications. The primary novel innovation
in this paper is a detailed analysis of the existing state-of-the-art likelihood functions and a
likelihood function, based on a binary hypothesis, previously proposed by the authors. The algorithm
is tested on electro-optical imagery obtained from a variety of sensors at Georgia Tech, including the
GT-SORT 0.5m Raven-class telescope, and a twenty degree field of view high frame rate CMOS sensor.
In particular, a data set of an extended pass of the Hitomi Astro-H satellite approximately 3 days
after loss of communication and potential break up is examined.
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Date
2016-09
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