A New Generation Of Radars

Take a look at how our system is able to see what no radar has seen before

Optical Sensors Are Not Sufficient

Advanced Driver Assist Systems (ADAS) or fully autonomous vehicles rely on three main sensor technologies: camera, lidar and traditional radar. Cameras give rich textual information about the surroundings, but no accurate structural and velocity estimation. Lidars provide a good structural estimation of the environment but do not provide doppler measurement and are very expensive. Both camera and lidar fail in dusty environments as well as bad weather conditions, such as rain or fog.

Optical%20sensor%20blocked%20by%20bad%20weather
ARS430%20sample%20output

Traditional ADAS Radars Fall Short

Radars are relatively inexpensive compare to lidar. They are also robust in bad weather conditions and harsh environments. However, traditional automotive radars output very sparse detections with poor resolution, providing limited information about the structure of the environment and the shape of the objects.

Zendar's Software Defined Radar Is The Future Of Autonomy

At Zendar, we build intelligent radar systems that provide high fidelity information of the environment, enabling higher levels of autonomy and ADAS under all weather conditions.

SAR
CPU%20Car

A Central Processor Takes Radars To The Next Level

Gone are the days where individual radars function in isolation. Utilizing a satellite radar architecture, inexpensive radar front-ends transmit raw data to a centralized compute system and are processed holistically with Zendar's proprietary Combined Collaborative Imaging (CCI) software.

10x Resolution Boost

Similar to how cameras with larger aperture produce images with better resolution, CCI processes data from all radar front-ends holistically therefore increasing the effective antenna aperture and boosting resolution.

CCI