I. Introduction
Ranging capability is a key fundamental metric for evaluating the detection performance of LiDAR, directly defining the effective range of the system's digitization of the physical world.
In fields such as autonomous driving, industrial robotics, and high-precision surveying and mapping, ranging capability not only determines the system's safety boundaries and operational efficiency, but also reflects its detection gain and robustness in extracting weak signals in complex environments. Standardized testing of this capability is both a physical extreme verification of the optoelectronic link performance and a technical prerequisite for ensuring the stable deployment of products in real-world scenarios.

II. What is Ranging Capability?
Ranging capability refers to the limit distance range within which a LiDAR can detect a target object and form valid point cloud information under specific operating conditions (such as specific target reflectivity, ambient light intensity, probability of detection, etc.).
It mainly includes two core metrics: the maximum detection range (i.e., the theoretical optical limit at which the LiDAR can detect a target) and the minimum detection range (i.e., the closest boundary at which the LiDAR can stably detect). In practical applications, due to limitations of hardware timing circuits (such as the ToF range), the system's effective ranging range is often less than the optical maximum detection range. These three together define the effective operating interval of the LiDAR.

Figure 1: Schematic diagram of LiDAR ToF ranging range

Figure 1 clearly illustrates the effective ranging boundaries of an automotive LiDAR. 0.3m is the signal saturation blind zone, 200m is the upper limit of the ToF hardware range, and 250m is the theoretical optical detection limit. Since the nominal maximum detection range (250m) is greater than the ToF range (200m), the actual effective detection range of the LiDAR is from 0.3m to 200m.

III. Influencing Factors
The ranging capability of LiDAR is a comprehensive performance metric, jointly affected by three major categories of factors: target characteristics, environmental conditions, and the LiDAR's own hardware and algorithms. These factors do not act independently but are coupled with each other.
1. Target Characteristics
(1) Target Reflectivity
According to the LiDAR power equation (see formula below), with hardware ($P_t$, $A_r$) and environment ($\alpha$) fixed, the target detection distance $R$ is proportional to the square root of the target reflectivity $\sqrt{\rho}$ (i.e., $R \propto \sqrt{\rho}$). $$P_r = P_t \cdot \frac{A_r}{R^2} \cdot \rho \cdot \eta_{sys} \cdot \exp(-2\alpha R)$$ Symbol description:

• $P_r$: Received power.
• $P_t$: Peak transmitted power.
• $A_r$: Receiving aperture area.
• $R$: Target distance.
• $\rho$: Target reflectivity (core variable).
• $\eta_{sys}$: System optical efficiency.
• $\alpha$: Atmospheric extinction coefficient (rain and fog impact factor).

(2) Target Geometry and Orientation

• Angle of incidence: The angle between the laser beam and the normal to the target surface. The larger the angle, the smaller the effective reflection area and the weaker the echo signal (i.e., “angle attenuation”), and signal loss may occur due to specular reflection.
• Target size: Small targets at long distances (such as pedestrians and motorcycles) reflect fewer laser points, have a low signal-to-noise ratio, and are more difficult to stably detect and classify.

2. Environmental Conditions
The detection performance of LiDAR is highly dependent on the operating environment. External optical noise, atmospheric media, and co-frequency signals all limit the system's effective detection range and data reliability by degrading the signal-to-noise ratio (SNR):

• Background light interference: Strong background light (such as direct sunlight) introduces a large amount of random photon noise, drowning out weak target echoes, leading to a decrease in SNR and a significant reduction in effective detection range.
• Atmospheric attenuation effect: Suspended particles such as rain, fog, and haze scatter and absorb the laser, causing bidirectional attenuation of signal energy and inducing false echoes, resulting in a significant decrease in detection accuracy and range.
• Co-band interference: When multiple radars of the same frequency operate simultaneously, the receiving end may mistakenly receive asynchronous pulse signals, generating ghost points or noise points, which seriously weakens the reliability of target recognition.

3. LiDAR System Itself (Hardware and Algorithms)

• Transmitting system: Power directly determines the upper limit of the range, but is constrained by eye safety regulations; wavelength (905nm/1550nm) determines the actual effective detection range by affecting the safe power threshold and atmospheric penetration.
• Receiving system: Sensitivity determines the ability to capture weak echoes; the higher the sensitivity, the deeper the long-distance detection; dynamic range determines the linear interval of the signal; the wider the range, the better it can prevent saturation of close-range strong targets and ensure stable ranging across the full range.
• Optical system: The receiving aperture determines the photon collection efficiency; the larger the aperture, the higher the echo signal-to-noise ratio (SNR), thereby directly enhancing the ranging capability for long-distance targets.
• Signal processing and algorithms: Detection thresholds balance false alarms and missed detections, defining the detection limit; anti-interference algorithms suppress noise crosstalk, ensuring ranging robustness under complex operating conditions; ToF accuracy determines the distance calculation accuracy, ensuring the authenticity and validity of long-distance point clouds.

IV. How to Test the Ranging Capability of LiDAR?
In autonomous driving scenarios, ranging capability refers to the distance under a specific POD. POD (Probability of Detection) determines the continuity and authenticity of the point cloud output at that distance. The following details the test conditions, operational steps, and result determination methods for the ranging capability of automotive LiDAR in accordance with the relevant provisions of GB/T 45500-2025.
Test Conditions
Long-range detection capability:

Table 1: Environmental conditions for long-range detection capability test

Table 2: Test conditions for long-range detection capability test

Short-range detection capability:

Table 3: Test conditions for short-range detection capability test

Test setup:

Figure 2: LiDAR ranging test setup

Recommended Equipment:
The Automotive LiDAR Automated Testing System independently developed by Yanding, matching the test methods specified in the national standard GB/T 45500-2025, can fully automatically complete multiple test items such as ranging and angular resolution, achieving one-stop standardized verification from equipment control and data collection to report output. This system includes the core equipment required for testing the ranging capability of automotive LiDAR:

10% Diffuse Reflectance Panel	Automatic Target Switching Bracket	DUT Adjustment Mechanism	Linear Guide Rail

Operational Steps:
Long-range detection capability:
(a) Set up the test environment as required in Figure 2. Install the LiDAR on a high-precision turntable, and place a 10% reflectivity diffuse reflectance panel (dimensions see Table 2) at its horizontal test distance (see Table 2).
(b) Rotate the LiDAR around the ranging center. In any field of view area, face the center of the diffuse reflectance panel directly, record no less than 100 frames of point clouds, and calculate the probability of detection POD (valid points / theoretical points, valid points > 200) on the diffuse reflectance panel during this period.
© Increase/decrease the distance between the LiDAR and the diffuse reflectance panel by 1m each time, repeat the above operations and calculations until the maximum distance satisfying a probability of detection greater than 50% is obtained, and then sequentially measure the maximum distance satisfying a probability of detection greater than 50% in other field of view areas of the LiDAR.

Short-range detection capability:
(a) Set up the test environment as required in Figure 2. Install the LiDAR on a high-precision turntable, and place a 10% reflectivity diffuse reflectance panel (dimensions see Table 3) at its horizontal test distance (see Table 3).
(b) Rotate the LiDAR around the ranging center. In any field of view area, face the center of the diffuse reflectance panel directly, record no less than 100 frames of point clouds, and calculate the probability of detection POD (valid points / theoretical points, valid points > 200) in the area of ±5 resolutions (nominal) from the center of the diffuse reflectance panel.
© Increase/decrease the distance between the LiDAR and the diffuse reflectance panel by 0.1m each time, repeat the above operations and calculations until the minimum distance satisfying a probability of detection greater than 50% is obtained, and then sequentially measure the minimum distance satisfying a probability of detection greater than 50% in other field of view areas of the LiDAR.

Result Determination:
The maximum detection range of the LiDAR shall not be less than the nominal value, and the minimum detection range shall not be greater than the nominal value, to meet the standard requirements.