According to Memes Consulting, the growing competition between LiDAR and other sensor technologies—such as cameras, radar, and ultrasound—is pushing the industry toward more advanced sensor fusion techniques. This not only increases the demand for accurate data integration but also highlights the importance of selecting high-quality photodetectors, light sources, and MEMS micromirrors to ensure optimal performance in autonomous systems.
As sensor technology, imaging capabilities, radar, LiDAR, electronics, and artificial intelligence continue to evolve, dozens of advanced driver assistance system (ADAS) functions have become widely available. These include collision avoidance, blind spot monitoring, lane departure warnings, and parking assistance. These systems rely on sensor fusion to operate in sync, enabling fully automated vehicles to perceive their surroundings, alert drivers to potential hazards, and even take evasive actions independently when necessary.
For self-driving cars, the ability to accurately detect and identify objects at high speeds is essential. Using distance determination methods, these vehicles must rapidly create 3D maps of the road ahead within a 100-meter range and generate high-resolution images up to 250 meters away. In the absence of a human driver, the vehicle’s AI must make quick, intelligent decisions based on real-time data.
One of the fundamental techniques used in this process is Time-of-Flight (ToF), which measures how long it takes for a pulse of energy—whether ultrasonic, radio, or light—to travel from the vehicle to a target and back. Knowing the speed of the pulse through the air allows the system to calculate the distance to the object. LiDAR, which uses light pulses, is particularly effective due to its high angular resolution and precision.
When comparing ToF technologies, LiDAR stands out because it offers better angular resolution than radar, allowing it to distinguish closely spaced objects with greater accuracy. This is especially important in high-speed scenarios where there's limited time to react to potential dangers like head-on collisions.
In a ToF LiDAR system, a laser emits a short light pulse, which triggers an internal timing circuit. When the reflected light reaches the photodetector, the circuit stops, and the time difference between transmission and reception (Δt) is measured. This measurement is then used to calculate the distance to the object using the speed of light (c). However, the accuracy of this calculation depends on several factors, including the pulse duration (τ) and the timing jitter (δΔt).
The distance resolution (ΔR) is influenced by two main factors: the timing jitter (δΔt) and the spatial width of the pulse (w = cτ). If the desired resolution is 5 cm, δΔt needs to be around 300 picoseconds, and the pulse duration τ should also be approximately 300 ps. This means that ToF LiDAR requires photodetectors with minimal timing jitter and lasers capable of emitting very short pulses—often picosecond-level lasers, which are more expensive but provide higher precision.
Figure 1 illustrates how beam divergence varies depending on the ratio of the aperture size to the wavelength. Radar typically has a larger beam divergence, resulting in lower angular resolution, while LiDAR produces a narrower beam, allowing for more precise object detection. As shown, radar (black) struggles to differentiate between two vehicles, whereas LiDAR (red) can clearly distinguish them.
For automotive LiDAR designers, choosing the right laser wavelength is one of the most critical decisions. This choice is constrained by several factors, including eye safety, atmospheric interaction, available laser types, and compatible photodetectors.
The two most commonly used wavelengths in automotive LiDAR are 905 nm and 1550 nm. While 905 nm is advantageous because silicon-based photodetectors can efficiently detect it, making them cost-effective, 1550 nm is safer for the human eye, allowing for higher pulse energy and improved performance in terms of photon budget.
Wavelength also plays a role in atmospheric attenuation, scattering, and surface reflection, all of which vary with different conditions. In real-world environments, water absorption at 1550 nm is stronger than at 905 nm, leading to greater signal loss. Therefore, 905 nm may offer better performance in certain weather conditions, though the trade-off involves safety and power considerations.
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