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The word "radar" stands for radio detection and ranging. Radar is an electromagnetic system used to detect, locate, track and identify different objects within a certain area. Radar emits electromagnetic energy in the direction of the target to observe the target's echo. Targets can be ships, airplanes, celestial bodies, cars, etc. In the early days, radar systems were only used in the military field due to their large size and high cost. Due to the development of high-frequency integrated circuits and monolithic microwave integrated circuits, modern micro radar systems can be implemented on printed circuit boards or even integrated circuits [1-5]. The applications of radar systems have expanded to commercial areas, such as wall penetration detection [6-9], indoor positioning [10-13], biomedical applications [14,15] and driving assistance [16,17]. The subject matter of this book focuses on radar technology and its application in automobiles.
Radar is a key technology in modern vehicle safety systems. Automotive radar is a key sensor in advanced driver assistance systems and is used for adaptive cruise control, collision avoidance, blind spot detection, lane change assistance, parking assistance, etc. Figure 1.1 shows a typical automotive radar configuration on a vehicle. Long-range radar (LRR) mounted on the front of the vehicle is commonly used for adaptive cruise control. Mid-range radars mounted at the front and rear have wider coverage than the LRR and can be used for cross-traffic alert and lane-change assist. Corner-mounted short-range radar supports parking assist, obstacle/pedestrian detection and blind-spot monitoring. In practical applications, these radars often work together to provide more reliable detection results. In terms of operating frequency, the 24ghz band has been used for traditional automotive sensors. The 77 GHz band is already widely used for automotive radar due to spectrum regulations and standards set by the European Telecommunications Standards Institute and the U.S. Federal Communications Commission. The development of mainstream automotive radar has shifted to the 77GHz band, which allows radars with better resolution and smaller form factors.
Figure 1.1 Typical radar configuration of vehicles
Fully autonomous vehicles, which have evolved from driver assistance systems, have much higher requirements for sensors, especially for on-board radar. The Society of Automotive Engineers (SAE) has developed six generally accepted levels of autonomous vehicles based on the degree of human participation in driving [18], including level zero, which means there is no automation, but the vehicle is completely controlled by humans. Figure 1.2 shows the definition of driving automation levels.
Figure 1.2 SAE autonomous driving level
Level 1 (Driver Assistance): The human driver is responsible for all tasks related to vehicle operation, including accelerating, steering, braking and monitoring the surrounding environment. The car has a self-driving system that can help with steering or acceleration, but not both.
Level 2 (Partial Automation): At this level, automated systems in the car can assist with steering and acceleration, while the driver remains responsible for most safety-critical functions and environmental monitoring. Currently, Level 2 autonomous vehicles are the most common on the road.
Level 3 (Conditional Autonomous Driving): Starting from Level 3, the car itself monitors the environment through the use of autonomous vehicle sensors and performs other dynamic driving tasks such as braking. If a system failure or other unexpected situation occurs while driving, the driver must be prepared to intervene.
Level 4 (High Automation): Level 4 is associated with a high degree of automation, where the car is able to complete the entire journey without driver intervention, even in extreme situations. However, there are some limitations: the driver can only switch the vehicle into this mode when the system detects that the traffic conditions are safe and there are no traffic jams.
Level 5 (fully autonomous): Fully autonomous cars do not yet exist, but automakers are working toward Level 5 autonomy, in which the driver only needs to specify a destination and the vehicle takes full control and is responsible for all driving modes. Therefore, Level 5 autonomous vehicles will not have any provision for human control, such as a steering wheel or pedals.
The future of self-driving cars looks great; however, achieving a fully autonomous car is still very challenging. Currently, the market is still dominated by Level 2 partially autonomous vehicles.
Without sensors, self-driving cars would be impossible. Sensors allow cars to see and sense everything on the road and collect the information they need to drive safely. Additionally, this information is processed and analyzed in order to construct a path from point A to point B and send appropriate instructions to the car controller, such as steering, acceleration, and braking. Furthermore, information collected by sensors on autonomous vehicles, including the actual path ahead, traffic jams and any obstacles on the road, can also be shared between connected cars through vehicle-to-vehicle communication technology [19,20]. Very useful resource for driving automation. Most automakers today most commonly use the following three types of sensors in autonomous vehicles: cameras, radar, and lidar. Radar provides the position and velocity of a target at relatively low cost compared to other sensors. In addition, radar is also robust in harsh environments [21,22], such as low light, severe weather, and extreme temperatures. These characteristics make radar a unique sensor for autonomous vehicles.
Current automotive radar technology is mostly based on the principle of Frequency Modulated Continuous Wave (FMCW) radar, which has been known for decades. In this book, taking FMCW waveform as an example, the basic principles of modern automotive radar are first introduced. The spatial dimensions are obtained using modern multiple-input multiple-output technology (MIMO), which is described in the next chapter. With the addition of hardware features such as phase modulation, and the expansion of simultaneously utilized transmit and receive channels with independent modulation capabilities, new degrees of freedom are added to traditional FMCW radar system design and signal processing. As more and more vehicles adopt on-board radar, the radar will inevitably be interfered by other radars in the same frequency band. Chapter 4 will introduce interference and how to mitigate it. Chapter 5 describes how radar sensors can be integrated with other sensors to improve target detection capabilities. Chapter 6 gives several methods of using radar to classify common traffic targets. Then, in Chapter 7, the application of using radar for road surface condition detection will be discussed.
In this book we also recognize that the future of automotive radar should not only address traditional external applications, but also play an important role in internal applications such as gesture sensing for human-computer interaction, driver/passenger vital signs and presence monitor. Chapters 8 and 9 of this book cover these areas in detail.