IEEE - Aerospace and Electronic Systems - April 2022 - 22

Feature Article:
DOI. No. 10.1109/MAES.2021.3052312
Cross-Platform Radar Resource Management for
Coordinated Search and Tracking
Fotios Katsilieris and Bernhard Krach , Airbus Defense and Space GmbH,
85077 Manching, Germany
INTRODUCTION
Modern military aircraft have a suite of sensors that play a
crucial role for the aircraft and the pilot in order to accomplish
his mission efficiently. This suite comprises in its
most generic case a radar, an identification friend or foe
(IFF) system, an electro-optical/infrared (EO/IR) sensors,
and electronic support measures (e.g., laser and radar
warners).
Among these sensors, the radar is the primary sensor
for building and maintaining situational awareness due to
its capabilities. It can detect objects of interests (i.e., targets)
at very long ranges and is not limited severely by
weather conditions, as opposed to an EO/IR sensor. A
radar can execute tasks ranging from detection, tracking,
and classification of targets all the way down to altimetry
and weather sensing.
In this article, we will focus on the radar tasks of
searching for objects of interest and tracking them after
detection. Search means that a volume must be searched
such that there are no remaining aircraft undetected in it,
see Figure 1. Search is of paramount importance for the
situational awareness of a pilot. Undetected objects can be
a problem not only due to their potential hostility w.r.t.
the mission being executed but also due to potential collisions
in peacetime operations.
For each object that has been detected, a corresponding
tracking task is generated. Naturally, as more objects
Authors' current address: F. Katsilieris and B. Krach,
Airbus Defense and Space GmbH, 85077 Manching,
Germany (e-mail: Fotios.Katsilieris@airbus.com; Bernhard.Krach@airbus.com).
Manuscript
received September 30, 2020, revised
December 18, 2020; accepted December 21, 2020, and
ready for publication January 14, 2021.
Review handled by Josef Worms.
0885-8985/21/$26.00 ß 2021 IEEE
22
are being detected the need arises to balance radar resources
between tracking and search tasks.
Initially, aircraft were equipped with mechanically
scanned antenna radars. This implied that there were only
few parameters that could be optimized w.r.t. performing
search. A pilot would define the volume size, usually in
terms of azimuth and elevation extent, and the desired
range at which a target of a desired size [in terms of its
radar cross section (RCS)] should be detected. Given this
information, the radar would optimize the emitted waveforms.
The search pattern and the scan rate of the volume
would largely be fixed and only depend on the size of the
defined volume.
A modern aircraft, on the other hand, is being
equipped with radars with active electronically scanned
array antennas, commonly abbreviated as AESA radars.
Such radars are more flexible than their predecessors,
mechanically steered radars. AESA radars can steer their
beam almost instantaneously between two three-dimensional
(3-D) angles, which makes adaptive beam pointing
possible. This is a major advantage over mechanically
steered radars.
The control of single AESA radars have been considered
in numerous publications in the literature. Recently,
a trending topic is the control of networked (also called
netted) AESA radars, see, for example [1]-[4]. A review
of the most recent papers on this topic follows below.
In [5], the authors deal with the optimization of tracking
resources for multiple radars. In [6], the authors
address the problem ofjointly positioning radars and tuning
their modes in order to optimize search performance.
In [7] and [8], the tracking task assignment problem for a
radar network is addressed. In [9], the authors use auctions
to solve the task assignment problem. In [10], the authors
provide a survey of state-of-the-art algorithms w.r.t. largescale
black-box optimization approaches based on CMAES
algorithm. In [11], the authors propose using and optimizing
a search grid pattern in order to optimize the
IEEE A&E SYSTEMS MAGAZINE
APRIL 2022

https://orcid.org/0000-0002-9405-9331 https://orcid.org/0000-0003-0448-878X https://orcid.org/0000-0002-9405-9331 https://orcid.org/0000-0003-0448-878X https://orcid.org/0000-0002-9405-9331 https://orcid.org/0000-0002-9405-9331 https://orcid.org/0000-0002-9405-9331 https://orcid.org/0000-0003-0448-878X https://orcid.org/0000-0003-0448-878X https://orcid.org/0000-0003-0448-878X

IEEE - Aerospace and Electronic Systems - April 2022

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