Aerospace & Defense Technology - December 2021 - 23

RF & Microwave Technology
of acoustic, radar, or other approaches
to detect the drone's location.
Airports
Whether criminal or innocent in intent,
drone sightings at airports increasingly
impact flight schedules. Not all
airports employ drone detection systems.
There is increasing concern over a
collision between an airplane and a
drone. You can use spectrum monitoring
approaches to mitigate the threat of
drones, detecting their presence and location
before damage occurs.
Drone manufacturers are working to
comply with airspace rules in more expensive
models that have restricted airspaces
programmed into them. In this
case, the drone controller receives a
message saying, " You are flying too
close to restricted airspace, " and the
drone will not fly into that space. To circumvent
that programming, a user
would have to hack the drone.
RF Emissions
The previous examples all share an intent
to harm. RF signals can also cause
unintentional damage. One common
issue often discussed is RF emissions.
Regulations for the communications industry
exist to eliminate their potential
health effects. In the cellular industry,
for example, rules cover emissions from
devices as well as network infrastructure.
By employing spectrum monitoring systems,
you can ensure that a cell tower is
broadcasting a signal at the correct
strength. This process relies on the government's
available tables and emission
levels for various frequencies. By setting
up limit lines in the monitoring system,
you can match those specifications. If
the RF energy at any site exceeds the levels,
you can have the system set off an
alarm or send a notification. Such solutions
are usually employed in response
to concern over a new tower or to test
signal strength at a specific location.
Testing in Anechoic Chambers
Thorough testing of smaller devices
and solutions benefits from the use of
anechoic chambers. These chambers are
completely sealed so that no outside RF
energy can enter. After placing a product
in an anechoic chamber, very sensitive
antennas measure the radiation
coming from the product. You can spin
the product around, pointing the antenna
at different angles - horizontal
and vertical polarization - and measure
the amount of RF energy radiating
from the box. You can use this process
to classify if a product is Class A or Class
B (whether it is usable in an industrial
setting or a home or small office). By
sweeping across the wide area of the
spectrum, you can measure the emissions
coming from your products. If
they do not meet a classification, you
can determine how to provide better
shielding, lower the noise level, or some
other solution.
You can also use anechoic chambers
to test susceptibility by bombarding
products with different types of outside
RF energy. You can test the effects
of various signals on product perfor -
mance using this process. While RF
emissions are important, the impact of
signals transmitted into the product
can significantly degrade performance.
Shielding must be effective on both the
transmit and receive ends.
Some RF emission regulations cite a
specific procedure or piece of equipment
to make mea surements. As a result,
manufacturers or engineers might
not want to use an anechoic chamber
because the work involves changing
the equipment versus the documented
recommendation. The opposite problem
is also quite common, whereby lab
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equipment is not updated. If the only
option is traditional swept technology,
you will spend most of the time searching
for the specific frequency. This approach
also misses a considerable
amount of spectrum events and details.
By using a modern fast Fourier transform
(FFT) analyzer instead, you get almost
the whole spectrum in one snapshot
instead of only a small portion as
you sweep across.
Summary
In today's world, RF signals can intentionally
inflict damage, as seen in the
examples of an EMP attack, drones, and
explosive devices. At this point, the
ability to foresee such attacks is mostly
beyond our technical capabilities. Continuous
spectrum monitoring identifies
unusual behavior and chatter and requires
investigation to determine if it is
innocent or not. The key is to observe
trends and patterns in user behavior
across communications channels.
Going forward, machine learning and
AI will bring more intelligence to this
process, helping to store and process information
to identify anomalies sooner.
With more forewarning of significant issues
or planned attacks, you can act to
limit or eliminate damage much earlier.
This article was written by Nancy
Friedrich, Aerospace Defense Industry Solutions
Marketing, at Keysight Technologies,
Santa Rosa, CA. For more information,
visit http://info.hotims.com/79420-511.
23
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http://info.hotims.com/79420-511 http://www.aerodefensetech.com http://info.hotims.com/79420-922

Aerospace & Defense Technology - December 2021

Table of Contents for the Digital Edition of Aerospace & Defense Technology - December 2021

Aerospace & Defense Technology - December 2021 - Intro
Aerospace & Defense Technology - December 2021 - Sponsor
Aerospace & Defense Technology - December 2021 - Cov1
Aerospace & Defense Technology - December 2021 - Cov2
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Aerospace & Defense Technology - December 2021 - Cov3
Aerospace & Defense Technology - December 2021 - Cov4
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