Your behavior appears to be a little unusual. Please verify that you are not a bot.


Why radar is the future of autonomous transportation

June 1, 2021  - By

By Steven Hong, Founder and CEO, Oculii

Steven Hong, Founder and CEO, Oculii

Steven Hong, Founder and CEO, Oculii

Radar has been around since the late 19th century, but today it is poised to revolutionize how autonomous vehicles (AVs) navigate the road. From its nautical origins as a tool to detect the location of ships in heavy fog to being a cost-effective way to prevent collisions in self-driving cars, radar has a wide range of applications.

For more than 30 years, carmakers and drivers have embedded radar in vehicles to assist with automated cruise control, automatic emergency braking, parking, and more. This effective, hardy technology plays a critical role in the driver experience today, and the same hardware will be used to help AVs navigate the road soon.

I believe that the next chapter of radar use in vehicles will be in the AV market, where software powered by artificial intelligence (AI) will use radar sensors to read a vehicle’s surroundings and get riders safely to their destination.

Radar Is a Market-Proven Hardware Solution

Radar has been around for so long, and the sensors we rely on in our vehicles every day are so reliable, that most drivers are not even aware that they have radar to thank for the assist on their perfect parallel parking job.

In this era of auto innovation and smart tech, the benefits of turning to this proven hardware solution abound:

  • Radar can perform well in poor weather conditions.
  • It is cost-effective, especially when compared to lidar and camera-based options.
  • Thanks to its low power requirements, adding radar sensors does not significantly impact a vehicle’s energy budget.
  • It is market-proven hardware that is robust and reliable in the field.

While competing technologies such as lidar are still years away from demonstrating that they can stand up to weather conditions and the toll that mileage takes on equipment, there is no question that radar sensors are up for the challenges of the road.

The flip side of this coin is that we also have the benefit of knowing the limits of traditional radar technology: It has poor spatial resolution, limited sensitivity, and a narrow field of view. However, this hardware can be greatly enhanced with the right software boost.

An Oculii sensor placed at the front corner of a vehicle. (Photo: Oculii)

An Oculii sensor placed at the front corner of a vehicle. (Photo: Oculii)

Unlocking the Potential of Radar with AI

Until recently, the best way to improve radar technology was to add more antennas until you got the resolution quality you were seeking. While this approach solves the problem of resolution, it introduces two other problems:

  1. Adding antennas exponentially increases a radar’s complexity, power consumption and size, while only improving performance linearly.
  2. In turn, this added complexity significantly increases the radar’s cost.

Consider the F-35 fighter jet, which relies on a radar system that costs more than the jet itself. While adding antennas may be a reasonable solution for military-operated airplanes, the consumer AV market would never tolerate the consequent cost increases. However, there is a way that existing automotive radars can be augmented with AI software to improve resolution, without increasing cost, size or power.

In the same way that AI software transformed what the automotive manufacturers were able to achieve with camera hardware, AI software can revolutionize how radar hardware is used for navigation in AVs.

Traditional radar sensors emit a constant, repetitive signal that delivers a reliable but low-resolution result. By using innovative AI software to emit an adaptive phase, modulated waveform that changes in real time, the resolution of traditional radar can be increased by up to 100 times. The key to transforming how we use radar hardware is all in the software.

street view of a driving car (center). At right, the same view is shown with high-resolution radar, with 400+ m of range with precise Doppler/point in all weather conditions. At left, is the view using a standard lidar camera, which has >100 m of range, no Doppler and weather limitations. (Image: Oculii)

street view of a driving car (center). At right, the same view is shown with high-resolution radar, with 400+ m of range with precise Doppler/point in all weather conditions. At left, is the view using a standard lidar camera, which has >100 m of range, no Doppler and weather limitations. (Image: Oculii)

Radar with AI

Reliable sensors with AI software can enable autonomous functions by augmenting the hardware that is already in today’s vehicles. What makes this solution so exciting is that it does not require a design overhaul: the smart sensors in question fit within existing radar packaging.

Augmenting radar hardware with AI can significantly improve performance while reducing the cost to the consumer. This formula — better performance at a lower price tag — has the potential to greatly accelerate the speed with which AVs make it safely to the consumer market and to revolutionize the automotive industry.

Rather than pushing forward with the development of costly alternatives that are prohibitively expensive for the consumer market, intelligent radar sensors can bring AVs to the road sooner and for more drivers.


Steven Hong is the founder and CEO of Oculii, a high-resolution radar company enabling the next generation of autonomous systems. Powered by AI, Oculii software increases the resolution of commodity radar hardware by up to 100 times and works in any environment.

About the Author:


Senior Editor Tracy Cozzens joined GPS World magazine in 2006. She also is editor of GPS World’s newsletters and the sister website Geospatial Solutions. She has worked in government, for non-profits, and in corporate communications, editing a variety of publications for audiences ranging from federal government contractors to teachers.

Comments are currently closed.