Ambarella, Inc. (NASDAQ: AMBA), an edge AI semiconductor company,
today announced the world’s first centralized 4D imaging radar
architecture, which allows both central processing of raw radar
data and deep, low-level fusion with other sensor inputs—including
cameras, lidar and ultrasonics. This breakthrough architecture
provides greater environmental perception and safer path planning
in AI-based ADAS and L2+ to L5 autonomous driving systems, as well
as autonomous robotics. It features Ambarella’s Oculii™ radar
technology, including the only AI software algorithms that
dynamically adapt radar waveforms to the surrounding
environment—providing high angular resolution of 0.5 degrees, an
ultra-dense point cloud up to 10s of thousands of points per frame
and a long detection range up to 500+ meters. All of this is
achieved with an order of magnitude fewer antenna MIMO channels,
which reduces the data bandwidth and achieves significantly lower
power consumption than competing 4D imaging radars. Ambarella’s
centralized 4D imaging radar with Oculii technology provides a
flexible and high performance perception architecture that enables
system integrators to future proof their radar designs.
Watch our short video here:
https://www.globenewswire.com/NewsRoom/AttachmentNg/fa354596-e725-4ec8-b0fc-fe7be3aae244
“There were ~100M radar units manufactured in 2021 for
automotive ADAS,” explains Cédric Malaquin, Team Lead
Analyst of RF activity at Yole Intelligence, part of Yole
Group. “We expect this volume to grow 2.5-fold by 2027,
given the more demanding regulations on safety and more advanced
driving automation systems hitting the road. Indeed, from the
current 1-3 radar sensors per car, OEMs will move to 5 radar
sensors per car as a baseline (1). Besides, there is an exciting
debate on the radar processing partitioning and many developments
associated. One approach is centralized radar computing that will
enable OEMs to offer significantly higher performance imaging radar
systems and new ADAS/AD features while simultaneously optimizing
the cost of radar sensing.”
To create this unique, cost-effective new architecture,
Ambarella optimized the Oculii algorithms for its CV3 AI domain
controller SoC family and added specific radar signal processing
acceleration. The CV3’s industry-leading AI performance per watt
offers the high compute and memory capacity needed to achieve high
radar density, range and sensitivity. Additionally, a single CV3
can efficiently provide high-performance, real-time processing for
perception, low-level sensor fusion and path planning, centrally
and simultaneously, within autonomous vehicles and robots.
“No other semiconductor and software company has advanced
in-house capabilities for both radar and camera technologies, as
well as AI processing,” said Fermi Wang, President and CEO of
Ambarella. “This expertise allowed us to create an unprecedented
centralized architecture that combines our unique Oculii radar
algorithms with the CV3’s industry-leading domain control
performance per watt to efficiently enable new levels of AI
perception, sensor fusion and path planning that will help realize
the full potential of ADAS, autonomous driving and robotics.”
The data sets of competing 4D imaging radar technologies are too
large to transport and process centrally. They generate multiple
terabits per second of data per module, while consuming more than
20 watts of power per radar module, due to thousands of MIMO
antennas used by each module to provide the high angular resolution
required for 4D imaging radar. That is multiplied across the six or
more radar modules required to cover a vehicle, making central
processing impractical for other radar technologies, which must
process radar data across thousands of antennas.
By applying AI software to dynamically adapt the radar waveforms
generated with existing monolithic microwave integrated circuit
(MMIC) devices, and using AI sparsification to create virtual
antennas, Oculii technology reduces the antenna array for each
processor-less MMIC radar head in this new architecture to 6
transmit x 8 receive. Overall, the number of MMICs is drastically
reduced, while achieving an extremely high 0.5 degrees of joint
azimuth and elevation angular resolution. Additionally, Ambarella’s
centralized architecture consumes significantly less power, at the
maximum duty cycle, and reduces the bandwidth for data transport by
6x, while eliminating the need for pre-filtered, edge processing
and its resulting loss in sensor information.
This cost-effective, software-defined centralized architecture
also enables dynamic allocation of the CV3’s processing resources,
based on real-time conditions, both between sensor types and among
sensors of the same type. For example, in extreme rainy conditions
that diminish long-range camera data, the CV3 can shift some of its
resources to improve radar inputs. Likewise, if it is raining while
driving on a highway, the CV3 can focus on data coming from
front-facing radar sensors to further extend the vehicle’s
detection range while providing faster reaction times. This can’t
be done with an edge-based architecture, where the radar data is
being processed at each module, and where processing capacity is
specified for worst-case scenarios and often goes
underutilized.
These two different approaches to radar processing are
summarized in the following table…
Competing Edge-Processed Radar |
Ambarella’s Centralized Radar Processing |
Constant, repeated radar waveforms without regard for environmental
conditions |
Oculii™ AI software algorithms dynamically adapt radar waveforms to
surrounding environment |
MMIC + edge radar processor in module |
MMIC-only in “radar head” |
Radar detection processing in radar module |
Radar detection processing in central processor |
Multiple terabits per second, per module of radar data (too large
to transport and process centrally) |
6x bandwidth reduction for radar data transport |
1+ to 2 degree resolution |
0.5 degrees of joint azimuth and elevation angular resolution |
High power consumption, due to 1000s of antenna MIMO channels used
by each radar module |
Low power consumption, due to order of magnitude fewer antenna MIMO
channels (6 transmit x 8 receive antennas in each processor-less
MMIC radar head) |
No dynamic processing allocation (specified for worst-case
scenarios) |
Dynamic allocation of CV3’s processing resources, based on
real-time conditions, between sensor types and among sensors of
same type |
Slow processing speeds |
CV3 is up to 100x faster than traditional edge radar
processors |
CV3 marks the debut of Ambarella’s next-generation CVflow®
architecture, with a neural vector processor and a general vector
processor, which were both designed by Ambarella from the ground up
to include radar-specific signal processing enhancements. These
processors work in tandem to run the Oculii advanced radar
perception software with far higher performance, including speeds
up to 100x faster than traditional edge radar processors can
achieve.
Additional benefits of this new centralized architecture include
easier over-the-air (OTA) software updates, for continuous
improvement and future proofing. In contrast, each edge radar
module’s processor must be updated individually, after determining
the processor and OS being used in each; whereas a single OTA
update can be pushed to the CV3 SoC and aggregated across all of
the system’s radar heads. These radar heads eliminate the need for
a processor, which reduces costs for both the upfront bill of
materials and in the event of damage from an accident (most radars
are located behind the vehicle’s bumper). Additionally, many of the
edge-processor radar modules deployed today never receive software
updates because of this software complexity.
Target applications for the new centralized radar architecture
include ADAS and level 2+ to level 5 autonomous vehicles, as well
as autonomous mobile robots (AMRs) and automated guided vehicle
(AGV) robots. These designs are streamlined by Ambarella’s unified
and flexible software development environment, which provides
automotive and robotics designers with a software-upgradable
platform for scaling performance from ADAS and L2+ to L5.
AvailabilityThis new centralized architecture
will be demonstrated at Ambarella’s invitation-only event taking
place during CES. Contact your Ambarella representative to schedule
a meeting. For sampling and evaluation information on the Oculii AI
radar technology and CV3 AI domain controller SoC family, contact
Ambarella: https://www.ambarella.com/contact-us/.
About AmbarellaAmbarella’s products are used in
a wide variety of human and computer vision applications, including
video security, advanced driver assistance systems (ADAS),
electronic mirror, drive recorder, driver/cabin monitoring,
autonomous driving and robotics applications. Ambarella’s low-power
systems-on-chip (SoCs) offer high-resolution video compression,
advanced image processing and powerful deep neural network
processing to enable intelligent perception, fusion and central
processing systems to extract valuable data from high-resolution
video and radar streams. For more information, please visit
www.ambarella.com.
Ambarella Contacts
- Media contact: Eric Lawson, elawson@ambarella.com, +1
480-276-9572
- Investor contact: Louis Gerhardy, lgerhardy@ambarella.com, +1
408-636-2310
- Sales contact: https://www.ambarella.com/contact-us/
1. Source: Radar
for Automotive report, Yole Intelligence, 2022
All brand names, product names, or trademarks
belong to their respective holders. Ambarella reserves the right to
alter product and service offerings, specifications, and pricing at
any time without notice. © 2022 Ambarella. All rights reserved.
A photo accompanying this announcement is available at
https://www.globenewswire.com/NewsRoom/AttachmentNg/34b95a6f-1a28-4f5a-83b7-d245b1980f12
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