Introduction
LiDAR, or light detection and ranging, is a common remote sensing method used to measure precise distances to objects on the Earth's surface. Although LiDAR was first deployed on aircraft in the 1960s, it did not become widely used until about two decades later. After the introduction of GPS in the 1980s, LiDAR became a standard approach for obtaining accurate geospatial measurements. Its applications have since expanded into many areas, and it is useful to understand LiDAR surveying technology and its working principle.
LiDAR technology
LiDAR uses pulsed laser light to compute variable distances between objects and the Earth's surface. Those light pulses, combined with information collected by an airborne system, generate accurate three-dimensional data about the terrain and target objects. A LiDAR instrument typically consists of three main components: a scanner, a laser, and a GPS receiver. Photodetectors and optical components also play important roles in data collection and analysis. Most government and private organizations acquire LiDAR data using helicopters, UAVs, and fixed-wing aircraft.
Types of LiDAR systems
LiDAR systems are broadly classified as airborne LiDAR and terrestrial LiDAR based on their deployment and function. Airborne LiDAR is mounted on helicopters or UAVs to collect data. When activated, an airborne LiDAR emits lasers toward the ground; reflected light returns immediately to the sensor, producing precise distance measurements. Airborne LiDAR can be further categorized as topographic LiDAR and bathymetric LiDAR.
By contrast, terrestrial LiDAR systems are mounted on mobile vehicles or tripods on the ground to collect accurate point measurements. These systems are common for road monitoring, infrastructure analysis, and collecting point clouds from building exteriors and interiors. Terrestrial LiDAR can be divided into mobile LiDAR and static LiDAR.
How LiDAR works
LiDAR follows a simple principle: it emits laser light toward objects on the Earth's surface and measures the time required for the light to return to the source. Given the speed of light (approximately 300,000 km/s), distance measurements using LiDAR are rapid. The standard formula used to compute an object's distance is:
Distance = (speed of light × time of flight) / 2
LiDAR supports many specific applications, including:
- Oceanography: LiDAR can determine precise ocean surface depths to locate objects or assist in investigations after maritime incidents. LiDAR can also be used to estimate phytoplankton fluorescence and surface biomass, measurements that were previously difficult to obtain.
- Digital elevation models: Ground elevation is critical for road construction, large buildings, and bridges. LiDAR provides x, y, and z coordinates, facilitating the creation of accurate 3D elevation models for engineering and planning.
- Agriculture and archaeology: Typical agricultural applications include yield estimation, crop condition analysis, and seed dispersion studies. LiDAR is also used for path planning and mapping forest canopies, among other tasks.
Beyond these uses, geoscientists employ LiDAR to investigate geomorphology, and military organizations use LiDAR for various border security tasks.
Single-line LiDAR: Triangulation vs ToF
When engineers select a LiDAR sensor for a robot, they often encounter large differences in appearance, performance parameters, and price across mechanical single-line LiDAR models from different manufacturers. These differences largely stem from the distance-measurement principle used. Mechanical single-line LiDAR sensors on the market typically use one of two ranging principles: triangulation or time of flight (ToF). Those differing principles lead to significant variations in size, performance, and cost.
The following sections describe both measurement methods in detail to help engineers choose the most suitable LiDAR approach for their application. First, triangulation-based LiDAR.
Triangulation-based LiDAR
The basic principle of triangulation-based LiDAR is shown in Figure 1. The ranging module emits an infrared laser toward the target. Part of the scattered light from the target is collected by the receiving lens and focused onto a line-scan image sensor (CCD or CMOS).
From the geometric relationship, targets at different distances produce laser spots that fall at different positions along the line sensor. The internal structure of the ranging module is fixed, and parameters such as the receiving lens focal length f and the baseline offset L between the emitter optical axis and the receiving lens principal axis are known. Using similar-triangle relationships, the distance D to the object can be computed.
The above description represents a simplified case. In practical designs, to improve distance resolution and make full use of the line sensor pixels, the emitter optical axis and the receiving lens principal axis are often set at a certain angle rather than parallel. The basic similar-triangle principle still applies. The triangulation principle implies several technical characteristics for LiDAR using this method.
First, consider measurement resolution. For triangulation LiDAR, distance resolution is closely related to measurement distance. Distance resolution is the ability to distinguish targets at different ranges; in other words, it is the minimum change in distance that produces a measurable change in the reported value. A key characteristic of triangulation is that this "ruler" has nonuniform graduations.
As Figure 1 shows, for near-range targets, a small change in distance causes a noticeable shift in the image location on the line sensor. For distant targets, even a large change in distance produces only a slight movement on the sensor. Thus, the distance resolution of triangulation degrades rapidly with range. This limits the practical maximum measurement distance for triangulation LiDAR; beyond that range the resolution drop makes measurements meaningless.
Next, consider measurement rate. A mechanical single-line LiDAR scans by rotating while measuring distances in different directions. Measurement rate directly determines how fast the device can scan (frame rate) and how many measurement points it outputs per revolution (angular resolution).
To achieve a given distance resolution, triangulation LiDAR typically uses high-resolution line sensors with thousands of pixels. Each distance measurement requires reading the pixel intensity values and passing them to a DSP for processing. The readout and processing time limit the data throughput of triangulation LiDAR.
Time-of-flight (ToF) LiDAR
ToF stands for time of flight. The basic ToF principle is shown in Figure 2:
- At the start of a measurement, a pulse driver drives the laser to emit an extremely short light pulse with very high instantaneous power, and the timing unit begins measuring.
- The emitted pulse reaches the target surface and is scattered in all directions. The receiving optics pick up part of the scattered energy and the photodetector converts it into photocurrent, which is sent to the echo signal processing circuit.
- The echo processing circuit converts the photocurrent to a voltage signal, amplifies and conditions it through one or more stages, and produces an electrical pulse corresponding to the echo. That pulse is used to trigger the timing unit to stop timing.
- The recorded time interval represents the total time for the laser pulse to travel to the target and back. Multiplying that time by the speed of light and dividing by 2 yields the distance between the ranging unit and the target.
The ToF principle is easy to understand, but practical engineering implementation faces significant technical challenges. ToF systems operate under extreme signal conditions: very large signals at the transmitter peak, very weak returned echoes, and extremely fast timing requirements at the nanosecond or picosecond scale. These constraints place high demands on driver capability, analog bandwidth, and noise suppression. However, once those challenges are addressed, ToF systems can deliver very high performance.
From a range perspective, ToF can emit extremely short pulses with high instantaneous power while meeting eye-safety limits, enabling detection of much more distant targets. Unlike triangulation, which relies on geometric similarity and whose resolution degrades with distance, ToF measures the pulse flight time, and timing precision does not depend on range. Thus, ToF distance resolution remains essentially constant across the operating range. Finally, ToF processes high-speed pulses, so each measurement takes very little time and very high measurement frequencies are readily achievable.
Which approach is better?
Choosing between triangulation and ToF single-line LiDAR depends on the sensor characteristics and the target use case.
Triangulation LiDAR is advantageous in cost, since the design is mature and can be manufactured cheaply at scale. However, its limited stability in some practical scenarios constrains its industrial use.
Because triangulation often uses a parallel-axis emitter and receiver layout, devices can be made low-profile, which suits applications with strict height constraints. Combined with higher short-range accuracy, triangulation LiDAR is well suited to consumer products. A common example is robotic vacuum cleaners: most navigation-capable models use triangulation single-line LiDAR as the primary sensor. Triangulation is also used in service robots when the operating environment is confined or when short-range obstacle avoidance is required.
ToF LiDAR systems are more complex than triangulation systems, so they tend to cost more, but they offer significantly better performance. Several development teams are working on ToF solutions that maintain industrial-grade stability and high performance while lowering system cost, potentially enabling ToF to replace triangulation LiDAR in some consumer applications.
Typical commercial ToF single-line LiDAR products have maximum measurement ranges starting around 10 m for 70% reflectivity targets, data rates of 15 kHz or higher, scanning frequencies from 15 Hz to 40 Hz, and many models can operate outdoors. This robustness to ambient light makes ToF suitable for mobile platforms that operate in large areas, move at higher speeds, or work in strong environmental illumination, such as outdoor environments. ToF is commonly used in service robots, AGV/AMR systems, and low-speed logistics vehicles. It is also used in static installations such as industrial safety systems, large-screen interaction, and security monitoring.
