IEEE - Aerospace and Electronic Systems - June 2021 - 20

Feature Article:
DOI. No. 10.1109/MAES.2021.3055958
An Ontology for Spaceborne Radar Debris Detection
and Tracking: Channel-Target Phenomenology and
Motion Models
Marco Maffei , Augusto Aubry , and Antonio De Maio , University of
Napoli Federico II, Napoli 80138, Italy
Alfonso Farina
, Selex ES, Roma 00131, Italy
INTRODUCTION
The environment around planet Earth comprises nonhomogeneous
and nonstationary fluxes of natural and manmade
junk, often referred to as " debris, " entailing possible
collision threats to strategic assets in space (e.g., orbital
infrastructure, spacecraft, and satellites) [1], [2]. It is
worth noting that the " space debris " term, also known as
" orbital debris, " has been defined by the Inter Agency
Space Debris Coordination Committee (IADC) as " ...all
man-made objects including fragments and elements
thereof, in Earth orbit or re-entering the atmosphere, that
are nonfunctional " [3]. In fact, the IADC definition does
not include natural (i.e., nonman-made) meteoroids,
whose size can oftentimes be negligible. For the sake of
clarification, both man-made and natural space junk could
be properly, and more generally, referred to as " Meteoroid
and Orbital Debris " (MOD). However, in order to adopt
common acronyms and terminology within the aerospace
community, both man-made and natural space junk can
also be jointly referred to using the " MicroMeteoroid and
Orbital Debris " (MMOD) term [3].
In this scenario, governments, armed forces, and space
agencies have set up space situational awareness (SSA)
programs aimed at monitoring as well as planning reaction
Authors' current addresses:MarcoMaffei, AugustoAubry,
and Antonio De Maio, University of Napoli Federico II,
80138 Napoli, Italy (e-mail: marco.maffei2@unina.it;
augusto.aubry@unina.it; ademaio@unina.it). Alfonso
Farina, Retired, Selex ES, 00131 Roma, Italy (e-mail:
alfonso.farina@outlook.it).
Manuscript received November 25, 2019, revised
September 9, 2020; accepted December 22, 2020, and
ready for publication January 28, 2021.
Review handled by Daniel O'Hagan.
0885-8985/21/$26.00 ß 2021 IEEE
18
capabilities for the protection of critical infrastructure in
space. Such operations are entrenched in difficulties in
terms of gauging capability and orbital trajectories prediction.
The former is related to current constraints of measurement
systems, whereas the latter is due to
uncertainties caused by gradients affecting debris dynamics,
chiefly during long observation campaigns [4]. Within
this framework, current data fusion systems for SSA are
fed with different types of data, oftentimes measured by
large ground-based radars (GBRs) (in addition to groundbased
and in-situ optical instruments), namely, in the very
high frequency (VHF) band [5], [6], ultrahigh-frequency
(UHF) band [5], [6], L-band [5]-[8], S-band [9], C-band
[8], X-band [5], [10], Ku-band [5], [10], as well as novel
measurements up to the W-band [11]. Accordingly, conventional
SSA operations are based on forming fence coverage
areas, which allow collecting detection contacts
when trespassed by a debris. In particular, this occurs by
monitoring large warped volumes of space relying on
either beam park or scanning modes (along with additional
experimental modes [7]). Moreover, for such monitoring,
there is an operative tradeoff between available transmit
peak-power and carrier frequency of the radar asset (in
other words, the larger the transmit peak-power, the lower
the transmit carrier frequency availability in terms of technology
readiness level).
Following the foregoing overview on SSA, this article
highlights limits and constraints of both GBRs and SpaceBorne
Radars (SBRs) to support SSA. It appears wise to
frame this problem adopting an ontological perspective on
the environmental scenario providing a structured representation
of concepts and relations thereof. In particular,
for radars supporting SSA (either GBRs or SBRs), the
goal is to highlight several ideas, categories, and properties,
as well as identifying possible connections among
these concepts with a focus on channel-target phenomenology
and motion models. Interestingly, the analysis of
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JUNE 2021
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