Autonomous Vehicle Engineering - July 2021 - 13

V2X
Mitigating
Radar-to-Radar
Interference
by Alessio Filippi, Francesco Laghezza, Feike Jansen, Jeroen Overdevest and Dilge Terbas
An effective radar interference mitigation strategy should
have the right balance between complexity and capability for
dealing with the interferers.
Sensors are a fundamental building block of
highly-automated and autonomous-driving vehicles.
And each different sensor - radar, lidar, and camera
systems - has strengths and weaknesses. Radars are
typically more robust than cameras to adverse weather
conditions. They're also more cost-effective than lidar,
and provide a better velocity and distance resolution.
However, typical drawbacks can be lower angular or
cross-range resolution and radar-to-radar interference.
There are advanced solutions that further increase
the radar angular resolution, from sparse arrays to
super-resolution algorithms. Solutions also exist to
improve the radar's sensitivity to distinguish small
targets from strong targets nearby, such as a pedestrian
next to a large truck or a building. As more and more
vehicles are fitted with radar systems, interference is
of growing concern.
Radar interference is a well-recognized challenge.
As all radars use the same allocated frequency
spectrum, multiple radars may transmit at the same
time and frequency. If they also share a common visible
path, they will interfere with each other.
The MOre Safety for All by Radar Interference
Mitigation (MOSRIM) report is possibly the first
project to assess the severity of the radar interference
problem. A National Highway Traffic Safety
Administration (NHTSA) study builds on that and
adds different traffic scenarios to determine when and
how often interference happens.
Solutions exist to improve the radar's sensitivity to distinguish small targets
from strong targets nearby, such as a motorcyclist entering the FoV among
passenger vehicles and large trucks.
AUTONOMOUS VEHICLE ENGINEERING
July 2021 13
NXP

Autonomous Vehicle Engineering - July 2021

Table of Contents for the Digital Edition of Autonomous Vehicle Engineering - July 2021

Autonomous Vehicle Engineering - July 2021 - SPONSOR1
Autonomous Vehicle Engineering - July 2021 - CVR1
Autonomous Vehicle Engineering - July 2021 - CVR2
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Autonomous Vehicle Engineering - July 2021 - CVR3
Autonomous Vehicle Engineering - July 2021 - CVR4
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