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The Use of RADAR Technology in Autonomous Vehicles

Key Takeaways

  • In most autonomous vehicles, the combination of cameras, LiDAR, and RADAR form the primary set of sensors that provide imaging, detection, ranging, tracking, and sensing of the drive location for a seamless ride.

  • RADAR in autonomous vehicles operates at the frequencies of 24, 74, 77, and 79 GHz.

  • There are two types of RADAR for autonomous vehicular applications: impulse RADAR and frequency-modulated continuous wave (FMCW) RADAR. 

 Radars in autonomous vehicles

Tremendous innovation in the automotive industry has led to advancements in the autonomy levels of vehicles. The industry has witnessed the shift from human-driven vehicles to autonomous or self-driven vehicles. All automobile manufacturers are entering into autonomous vehicle manufacturing, and they are competing to bring the most sophisticated autonomous vehicles to the market. To do this, automobile companies are focusing on research and development in sensor technologies, as autonomous vehicles rely on numerous sensors for navigation. Some sensor technologies used in autonomous vehicle navigation are ultrasonic, LiDAR, RADAR, etc. The use of sensors in autonomous vehicles offers more precision and power, as they are a fundamental part of advanced driving assistance system (ADAS) in self-driven vehicles. Let’s further explore sensor applications in autonomous vehicles. 

Autonomous Vehicles and Sensors

With the help of sensors, autonomous vehicles ensure no human interaction is needed while driving. A wide range of sensors are used in autonomous vehicles to build reliable vision. The sensors help the self-driving vehicle to detect hurdles or blockages in the driving environment and to move without causing fatalities.

Different sensors function together to form an accurate detection system in autonomous vehicles.  In most autonomous vehicles, the combination of cameras, LiDAR (light detection and ranging), and RADAR (radio detection and ranging) form the primary set of sensors that provide the functionalities of imaging, detection, ranging, tracking, and sensing of the drive location for a seamless ride. These sensor functionalities overlap, which helps in detecting the three-dimensional shape, distance, and speed of nearby objects.

Let’s discuss the three primary sensors that help autonomous vehicles function. 

Camera Vision 

Cameras are the best sensor solution to give an accurate visual representation of an autonomous vehicle’s surroundings. In autonomous vehicles, cameras are fixed on all four sides—front, rear, right, and left—to give a 360° view. These cameras use wide and narrow fields of view to perceive both short-range wide view and long-range arrow view. Super-wide lenses are used in autonomous vehicles for capturing a panoramic view that assists with parking.

However, accurate camera visuals fail to give information regarding the distance of objects from autonomous vehicles. To determine the distance of objects from the vehicle, LiDAR technology is used. 


LiDAR uses laser beams (light waves) to determine the distance between two objects. In autonomous vehicles, LiDAR is mounted on top of vehicles and is rotated at high speed while emitting laser beams. The laser beams reflect from the obstacles and travel back to the device. The time taken for this to happen is used to determine the distance, shape, and depth of the obstacles surrounding the autonomous vehicle.

Even though LiDAR can catch the position, shape, size, and depth of an obstacle, they can get glitched by fake echoes showing far objects as near objects and vice versa. LiDAR fails to distinguish between multiple copies of laser signals and shows non-existent obstacles to autonomous vehicles. LiDAR does not function well in rain, snow, or fog. Therefore, RADAR technology is the best and most precise sensor for autonomous vehicles. 


The principle of operation for LiDAR and RADAR are the same, but instead of the light waves used in LIDAR, RADAR relies on radio waves. The time taken by the radio waves to return from the obstacles to the device is used for calculating the distance, angle, and velocity of the obstacle in the surroundings of the autonomous vehicle. 

RADAR in autonomous vehicles operates at the frequencies of 24, 74, 77, and 79 GHz, corresponding to short-range radars (SRR), medium-range radars (MRR), and long-range radars (LRR), respectively. They each have slightly different functions:

  • SRR technology enables blind-spot monitoring, lane-keeping assistance, and parking assistance in autonomous vehicles. 

  • MRR sensors are used when obstacle detection is in the range of 100-150 meters with a beam angle varying between 30° to 160°. 

  • The automatic distance control and brake assistance are supported by LRR radar sensors. 

RADAR technology in autonomous vehicles operates with millimeter waves and offers millimeter precision. The utilization of millimeter waves in autonomous vehicular RADAR ensures high resolution in obstacle detection and centimeter accuracy in position and movement determination. Compared to other sensor technologies in autonomous vehicles, RADAR works reliably under low visibility conditions such as cloudy weather, snow, rain, and fog. 

Types of RADAR Used in Autonomous Vehicles

There are two types of RADAR used in autonomous vehicles. 

  1. Impulse RADAR - In impulse RADAR, one pulse is emitted from the device and the frequency of the signal remains constant throughout the operation.
  2. Frequency - modulated continuous wave (FMCW) RADAR - In FMCW RADAR, pulses are emitted continually. Pulses are modulated over the entire operation and the frequency varies over the transmission time. 

FMCW RADAR is dominant in autonomous vehicles due to its high resolution in range and depth perception. Extensive research studies by automobile manufacturers will continue to develop advanced variants of impulse and FMCW RADAR. Cadence software offers simulation tools to develop end-to-end radar systems not only for autonomous vehicles but also for aerospace, defense, and commercial applications.

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