Ultrasonic, Laser, Millimeter Wave: Talking about the “Three Musketeers” of Radar in Autonomous Driving

At present, there are three main types of radars used in unmanned vehicles: ultrasonic radar, lidar and millimeter-wave radar. Although the latter two radar technologies are rising stars, they have played an increasingly prominent role in autonomous driving in recent years.

Author: Dr. M

Every year, 1.25 million people die in car crashes, and more than 94% of fatal crashes are caused by human error (drink driving, speeding, ignoring traffic lights, texting while driving). To reduce auto accidents as close to zero as possible, automakers, auto suppliers, government, academia, and even non-automotive technology providers are working together to develop advanced driver assistance systems (ADAS) and eventually develop Self-driving cars. The establishment of a new automotive ecosystem such as autonomous vehicles requires the support of various advanced technologies such as sensor fusion, a new automotive network architecture, and the Internet of Vehicles.

At present, there are three main types of radars used in unmanned vehicles: ultrasonic radar, lidar and millimeter-wave radar. Although the latter two radar technologies are rising stars, they have played an increasingly prominent role in autonomous driving in recent years.

Figure 1: Sensor fusion scheme in self-driving cars (Image source: Internet)

01 Ultrasonic radar: mature technology, cost-effective choice

Ultrasonic radars have been used in automobiles for many years, and they can be found on the front and rear sides of many vehicles. Divided by operating frequency, ultrasonic radar has three types: 40kHz, 48kHz and 58kHz. The higher the frequency, the higher the sensitivity and the smaller the detection angle. In the working state, by sending and receiving ultrasonic waves, the ultrasonic radar can measure obstacles within a range of 0.2-5m with an accuracy of 1-3cm.

However, since the operating frequency belongs to the acoustic range, the shortcomings of ultrasonic radar are also obvious. Especially in the process of high-speed driving, due to the propagation delay of ultrasonic signals, there will be a certain delay in the received information. In addition, ultrasonic equipment also has the problem of poor directivity, requiring more equipment to cover the same area, and weather conditions can greatly affect their detection effect.

However, this has not affected the application of ultrasonic radar in the automotive industry. The key point is its high cost performance. The price of a single ultrasonic radar on the market is only tens of RMB. According to the calculation of installing 4 ultrasonic radars in a reversing radar system, the hardware cost is less than 200 RMB. Although the automatic parking system requires more ultrasonic radars, the total hardware cost can be controlled at about 500 yuan. Compared with LiDAR, which costs tens of thousands or even hundreds of thousands of yuan at every turn, the cost advantage of ultrasonic radar is too prominent. It is said that Tesla has a special preference for ultrasonic radars, using 8 for parking assistance and 12 for assisted driving.

02 Lidar: indispensable for autonomous driving

LiDAR (light detection and ranging, LiDAR), which means laser detection and ranging, is a sensing technology that emerged after radar and sonar, using laser pulses to scan the environment instead of radio waves or sound waves, with a wavelength of nanoscale. Of all the sensing technologies used in cars, lidar is a novelty and has a pivotal role in self-driving cars.

Lidar can provide the most accurate three-dimensional map and can scan 360-degree space around the self-driving car at a range of about 100 meters. Some lidar systems even offer as many as 64 channels, scanning over a million points per second. This amount of information provides a high accuracy of 2 centimeters to cope with changing environments. In addition to obtaining position information, the reflectivity of the laser signal can also distinguish the material of the target material.

According to the function, lidar systems can be divided into two categories: airborne lidar (Airborne LiDAR) and terrestrial lidar (Terrestrial LiDAR). Airborne lidars are mainly installed on helicopters or drones for data collection. Ground-based lidar systems are typically mounted on a moving vehicle or on a tripod on the ground to collect accurate data points. Self-driving cars use mobile ground-based lidar systems that use just one lidar to scan multiple angles at the speed of light at the same time to create a detailed 3D image or map of the surrounding area.

Because lidar uses lasers and mirrors for echo imaging and maps the surrounding environment in real time, its measurement accuracy is significantly higher than ultrasonic radar. Today, lidar is used in many critical automotive and mobile applications, including advanced driver assistance systems (ADAS) and autonomous driving systems. In practical applications, the technique can be combined with other sensory data to provide more reliable representations of static and moving objects in the vehicle environment.

Overall, extremely high resolution and accuracy, fast and intuitive test results, are the advantages of lidar for autonomous vehicles. To talk about the shortcomings, the current lidar is still large and expensive, which is also an important reason why lidar technology is difficult to apply on a large scale in the automotive industry.

03 Millimeter wave radar: moving towards 77-79GHz

Compared with the complex mirrors and lasers of lidar, the device of millimeter-wave radar is much simpler, but its signal transmission speed is faster and more accurate than ultrasonic. Millimeter-wave radars typically operate at 24GHz and 77-79GHz and are largely unaffected by environmental factors such as heat or light. Millimeter-wave antennas are also much smaller and less powerful than ultrasonic antennas, making them easy to integrate into vehicle designs. Additionally, they can be adjusted to short, long, wide or narrow detection ranges to meet the needs of specific applications.

Traditional 24 GHz narrowband automotive radar has certain limitations in distinguishing objects and distinguishing between people, dogs, other cars, etc. At present, the automotive radar sensing technology with 24GHz narrowband sensor as the mainstream is developing rapidly in the direction of 76-81GHz frequency band, frequency modulated continuous wave (FMCW) and beamforming antenna. Among them, 76GHz is used for long-distance detection, and the 77-81GHz frequency band is used for short-distance, high-precision detection.

We know that distance measurement error and minimum resolvable distance are inversely proportional to bandwidth. Transitioning from 24GHz to 79GHz can improve performance in terms of range resolution and accuracy by nearly 20 times. That is to say, the distance resolution of the 24GHz system is 75cm. If it is replaced by the 79GHz system, the resolution will reach 4cm, which can better detect multiple adjacent objects. Likewise, at smaller wavelengths, the resolution and accuracy of velocity measurements will increase proportionally.

Another advantage of adopting a 79GHz radar system is that the size and weight of the equipment will be drastically reduced. Since the wavelength of a 79GHz signal is about one-third that of a 24GHz system, the total area of ​​a 79GHz antenna is only one-ninth that of a 24GHz antenna. Developers can use smaller and lighter sensors and easily hide them for better fuel economy and car form factor. It can be said that the 76-81GHz millimeter-wave radar is a sensing technology for future ADAS and autonomous driving.

04 Fusion of Automotive Sensing Technology

In addition to the above three sensing technologies, vehicle cameras are also sensors widely used in automobiles. Due to space limitations, this article does not introduce them in detail. It is undeniable that in current vehicles, onboard cameras act as the primary visual sensor for ADAS systems. The image is collected by the lens and processed by the photosensitive components and control components in the camera, and then converted into a digital signal for further processing by the computer, so as to realize the perception of road conditions around the vehicle, including forward collision warning, lane deviation Alarm, pedestrian detection and other functions.

Any kind of sensing technology has its advantages and limitations, and the automotive industry will not rely on only one sensing technology to realize its autonomous driving function. Most manufacturers combine these three sensing technologies to ensure that their autonomous driving systems receive reliable data in terms of range, resolution and robustness. While current sensing solutions do not yet provide enough data to enable fully autonomous driving, they have greatly reduced driver human error through ADAS systems.

In turn, the adoption of ADAS technology and the emergence of driverless cars have further contributed to the development of automotive sensor technology and markets. According to market research firm MarketsandMarkets, the automotive sensor market will grow from $24.5 billion in 2020 to $40.3 billion by 2025, with a compound annual growth rate of 10.5% between 2020 and 2025. Global vehicle production and increasing demand for vehicle electrification, including rising consumer demand for vehicle safety and comfort, are the major factors driving the growth of the automotive sensor market.

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