Aerospace & Defense Technology - May 2022 - 6

UAV Navigation Systems
Forecast Risk Analysis best- and worst-case scenarios for downtown Indianapolis.
interference is an extremely hard problem
to solve - certainly at a cost that's
viable for drone applications at scale.
What if instead of " fixing " GNSS reliability
by using other sensors and signals,
we could just predict exactly
where and when it will be degraded?
Wouldn't that mitigate most of these
issues? Or even enable performance
improvements? That's exactly what
new GNSS prediction technologies are
doing. And they're about to upend the
status quo for many of today's most
important aviation use cases, as well as
tomorrow's.
GNSS Limitations
GNSS has come a long way since the
early days of Navy Transit testing in the
1960s. But the technology still has some
baked-in challenges - like the fact that
constellations of satellites transmitting
navigation signals are constantly in
motion. Those satellites orbit the Earth
at about one degree per minute, transmitting
some 22,000 kilometers down
to a given aircraft's (or vehicle's, or
device's) receiver. So, the strength and
reliability of GPS or other GNSS signals
can change literally every second.
For aircraft flying at high altitudes,
that's not a problem; they'll typically
communicate with up to a dozen satellites
at once. Closer to the ground though, terrain
and buildings can deteriorate GNSS
6
signals or block them altogether. The
problem becomes particularly thorny:
* At altitudes below 400 feet: Here, aircraft
must navigate far more dynamic
environments, especially in urban and
suburban areas, with clear views of
navigation satellites frequently
obstructed by buildings and terrain.
* When flying beyond visual line of
site (BVLOS): The Federal Aviation
Administration (FAA) has deemed GPS
navigation so critical to flying BVLOS,
most FAA BVLOS waivers require
drone operators to immediately land
aircraft if GNSS degrades or is lost. The
policy is understandable, but it's
become a significant handcuff for
technology leaders trying to test new
drone business models, much less
actually put them into production.
* When trying to manage unmanned
air traffic: With no awareness of terrain
or buildings, GNSS as currently
implemented cannot be relied on for
the safe management of a dynamic
automated airspace - certainly not
one where thousands of drones navigate
densely populated areas.
It's not that these problems are entirely
insurmountable. Drones (and other
autonomous vehicles and devices) can
augment navigation with better inertial
systems, additional sensors and cameras,
radar, and other workarounds. But
mobilityengineeringtech.com
ADT Feature 1 - UAV Navigation Systems 0522_1.indd 6 Intro
Cov
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these add significant cost and weight,
making them impractical for drone use
cases at any kind of scale. None offer a
100% reliable solution either. Bottom
line: if we're going to unleash the new
civil and military drone applications
that technologists envision, we must
find a practical way to get more reliable
navigation. If this can be done by leveraging
existing, inexpensive technologies
- all the better.
Enter GNSS Prediction
Military and civilian engineers have a
long history of solving the most difficult
technology problems. But sometimes,
the cleverest innovations arise
when engineers recognize that even if
they can't solve a problem directly, they
can get to results that are almost as useful.
We might not be able to guarantee
reliable GNSS signals everywhere that
aircraft need them with current technology.
One thing we can do, however,
is predict exactly where and when GPS/
GNSS data will be unreliable or unavailable.
That's exactly what technology
leaders in this space are now doing.
New GPS/GNSS prediction techniques
can analyze line-of-sight to each individual
satellite over a service area, across
every square meter of that area, every
second, in four dimensions. These
cloud-based solutions ray-trace up to
individual satellites to identify every
Aerospace & Defense Technology, May 2022
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Aerospace & Defense Technology - May 2022

Table of Contents for the Digital Edition of Aerospace & Defense Technology - May 2022

Aerospace & Defense Technology - May 2022 - Intro
Aerospace & Defense Technology - May 2022 - Cov 4
Aerospace & Defense Technology - May 2022 - Cov 1
Aerospace & Defense Technology - May 2022 - Cov 2
Aerospace & Defense Technology - May 2022 - 1
Aerospace & Defense Technology - May 2022 - 2
Aerospace & Defense Technology - May 2022 - 3
Aerospace & Defense Technology - May 2022 - 4
Aerospace & Defense Technology - May 2022 - 5
Aerospace & Defense Technology - May 2022 - 6
Aerospace & Defense Technology - May 2022 - 7
Aerospace & Defense Technology - May 2022 - 8
Aerospace & Defense Technology - May 2022 - 9
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Aerospace & Defense Technology - May 2022 - 48
Aerospace & Defense Technology - May 2022 - Cov 3
Aerospace & Defense Technology - May 2022 - Cov 4
https://www.nxtbook.com/smg/techbriefs/22ADT10
https://www.nxtbook.com/smg/techbriefs/22ADT09
https://www.nxtbook.com/smg/techbriefs/22ADT08
https://www.nxtbook.com/smg/techbriefs/22ADT06
https://www.nxtbook.com/smg/techbriefs/22ADT05
https://www.nxtbook.com/smg/techbriefs/22ADT04
https://www.nxtbook.com/smg/techbriefs/22ADT02
https://www.nxtbook.com/smg/techbriefs/21ADT12
https://www.nxtbook.com/smg/techbriefs/21ADT10
https://www.nxtbook.com/smg/techbriefs/21ADT09
https://www.nxtbook.com/smg/techbriefs/21ADT08
https://www.nxtbook.com/smg/techbriefs/21ADT06
https://www.nxtbook.com/smg/techbriefs/21ADT05
https://www.nxtbook.com/smg/techbriefs/21ADT04
https://www.nxtbook.com/smg/techbriefs/21ADT02
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