With the growing excitement around autonomous driving, laser radar has become highly sought after due to its high precision, large data output, and immunity to visible light interference. However, it's interesting to note that mainstream autonomous driving systems still rely on millimeter-wave radar. Why is that? Let’s explore.
First, let's clarify what we mean by radar. In this context, we're referring to a radar system that emits electromagnetic waves, not a mechanical wave-based reversing radar.
Radar technology originated during World War II, initially used to detect enemy aircraft crossing the English Channel. It played a crucial role in military operations, from spotting enemy ships in the Pacific to detecting anti-radiation missiles in the Bekaa Valley. After the war, radar found its way into the automotive industry, becoming an essential tool for drivers.
Today, radar is a key sensor in advanced driver assistance systems (ADAS). It helps with adaptive cruise control, blind spot monitoring, and automatic emergency braking—making it an indispensable part of modern vehicles.
Now, let's look at the structure and working principle of on-board radar. Most car radars operate in the 24 GHz or 77 GHz frequency bands. The 77 GHz band is considered the future, as it's specifically allocated for vehicle radar by the International Telecommunication Union. While 24 GHz radars are also classified as millimeter-wave radars, the 77 GHz version offers better performance and is more widely used in modern systems.
In practice, planar antenna arrays are commonly used in vehicle radars because they are compact, cost-effective, and don’t require moving parts. A typical flat-panel radar has multiple transmit and receive antennas arranged in specific patterns. For example, there might be 10 transmit antennas for short-range detection and 2 for long-range, while 4 receive antennas handle the signals.
The radar sends out directional beams, which vary in intensity depending on the direction. These beams help determine the position, speed, and direction of objects. The distance is calculated using the time it takes for the signal to return, while the Doppler effect helps measure the relative speed of the target.
For azimuth measurement, the phase difference between signals received by different antennas is analyzed. This allows the radar to determine the angle of the object relative to the vehicle.
Millimeter-wave radars have several key applications, including Adaptive Cruise Control (ACC), Blind Spot Detection (BSD), Lane Change Assist (LCA), and Automatic Emergency Braking (AEB). These systems rely on accurate data processing, where radar signals are filtered, transformed using FFT, and then matched to identify and track objects.
One common question is whether radar can detect stationary objects. The answer is yes—but early ACC systems sometimes failed to react due to limitations in resolution and object classification. Modern systems now use advanced algorithms to distinguish between infrastructure and actual traffic participants.
Another point of comparison: how does millimeter-wave radar stack up against lidar? While lidar offers higher precision and detailed 3D maps, it’s more expensive and less effective in adverse weather conditions like fog or rain. Millimeter-wave radar, on the other hand, works reliably in all weather and has a longer range, making it ideal for highway scenarios.
In summary, even though lidar is popular in autonomous driving, millimeter-wave radar remains a vital component due to its reliability, cost-effectiveness, and ability to perform in real-world conditions.
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