There is still some confusion in the industry about the different roles of the three main sensors (camera, radar and LIDAR) in the car and how each of them meets the sensing needs of advanced driver assistance systems (ADAS) and autonomous driving.
Level 4 and 5 autonomous vehicles may require cameras, LIDAR and radar to provide a high reliability and fully autonomous driving experience. However, for more economical Level 2 and 3 vehicles that require partially autonomous driving and are already in mass production, imaging radar using TI’s mmWave sensors enables high performance and cost-effectiveness with broad adoption of ADAS capabilities . “
So, what is imaging radar?
Imaging radar is a subset of radar, so named because of its high angular resolution, which provides sharp images. Imaging radar is enabled by a sensor configuration in which multiple low-power TI mmWave sensors are cascaded together and operate synchronously as a unit. It features multiple receive and transmit channels that significantly improve angular resolution and radar range performance. When mmWave sensors are cascaded together, integrated phase shifters can be used to create beamforming, resulting in an extended range of 400 meters. The figure below shows the cascaded mmWave sensors and their antennas on the evaluation module.
An imaging radar evaluation module with four cascaded TI mmWave sensors
Millimeter Wave Technology for Imaging Radar
A typical radar sensor has only recently been considered the primary sensor in a vehicle, mainly due to its limited angular resolution performance.
Angular resolution refers to the ability to distinguish objects within the same range and at the same relative velocity. A common use that highlights the benefits of imaging radar sensors is the ability to identify stationary objects at high resolution. Typical mmWave sensors, with their high speed and high range resolution performance, can easily identify and differentiate moving objects, but their ability to identify static objects is very limited.
For example, in order for a sensor to “see” a stopped vehicle in the middle of a lane and distinguish it from a light pole or fence, the sensor needs some angular resolution in both elevation and azimuth.
The photo below shows a car trapped in a tunnel with smoke coming from the car. The vehicle was parked about 100 meters away and the tunnel height was 3 meters.
The front radar of an oncoming vehicle needs a high enough angular resolution to distinguish between tunnels and stopped vehicles. Millimeter wave sensors can penetrate any visibility situation, such as smoke.
How mmWave Sensors Use Multiple-Input Multiple-Output (MIMO) Radars to Achieve High Elevation Resolution
In order to identify a vehicle in a tunnel, sensors need to distinguish it from the tunnel roof and walls. Achieving scene classification takes advantage of these elevation and azimuth resolutions:
ɸ (elevation angle) = arctangent (2 m/100 m) = 1.14 degrees
ɸ (elevation angle) = arctangent (3.5 m/100 m) = 2 degrees
where 2 m is the height of the tunnel minus the height of the vehicle, 100 m is the distance between the oncoming vehicle with imaging radar and the vehicle parked in the tunnel, and 3.5 m is the distance between the vehicle parked in the tunnel and the tunnel wall distance.
Relying on other optical sensors can be challenging in certain weather and visibility conditions. Smoke, fog, inclement weather, and chiaroscuro are all challenging visibility situations that inhibit optical passive and active sensors, such as cameras and LIDAR, so that these sensors may fail to recognize objects. However, TI mmWave sensors maintain strong performance in poor weather and visibility conditions.
Imaging radar sensors are currently the only sensors that maintain robust performance in all weather and visibility conditions, with angular resolution of 1 degree in both azimuth and elevation (or even lower when using super-resolution algorithms to calculate values) ).
Imaging Radar from TI mmWave Sensors Offers High Flexibility
Imaging radars with TI mmWave sensors are highly flexible, capable of sensing and classifying objects in the near field with very high resolution, while tracking targets in the far field up to 400 meters away. This cost-effective high-resolution imaging radar system enables Level 2 and Level 3 ADAS applications as well as high-end Level 4 and Level 5 autonomous vehicles, and can be used as the primary sensor in the vehicle.
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