Laser rangefinders, LiDARs, and other devices are widely used in modern industries, surveying, autonomous driving, and consumer electronics. However, many users notice significant measurement deviations when operating in the field, especially when dealing with objects of different colors or materials. The root cause of this error is often closely related to the target’s reflectivity. This article will delve into the impact of reflectivity on distance measurement and provide practical strategies for target selection.
1. What is Reflectivity and Why Does It Affect Distance Measurement?
Reflectivity refers to the ability of a surface to reflect incident light, typically expressed as a percentage (e.g., a white wall has a reflectivity of about 80%, while black rubber has only 5%). Laser measurement devices determine distance by calculating the time difference between emitted and reflected light (using the Time-of-Flight principle). If the target’s reflectivity is too low, it can lead to:
- Weak Signal Strength: If the reflected light is too weak, the device cannot capture a valid signal.
- Increased Measurement Error: With higher noise interference, precision decreases.
- Shortened Measurement Range: The maximum effective distance can drop by more than 50%.
2. Reflectivity Classification and Target Selection Strategies
Based on the characteristics of common materials, targets can be classified into the following three categories:
① High Reflectivity Targets (>50%)
- Typical Materials: Polished metal surfaces, mirrors, white ceramics, light-colored concrete
- Advantages: Strong signal return, suitable for long-distance (over 500m) high-precision measurements
- Application Scenarios: Building surveying, power line inspections, drone terrain scanning
- Note: Avoid mirror surfaces that can lead to specular reflections (which may cause spot misalignment).
② Medium Reflectivity Targets (20%-50%)
- Typical Materials: Wood, asphalt roads, dark brick walls, green plants
- Countermeasures:
Shorten the measurement distance (recommended <200m).
Enable the device’s high-sensitivity mode.
Prefer matte surfaces (e.g., frosted materials).
③ Low Reflectivity Targets (<20%)
- Typical Materials: Black rubber, coal piles, dark fabrics, water bodies
- Risks: Signals may be lost or suffer from jump errors.
- Solutions:
Use a retro-reflective target (reflector boards).
Adjust the laser incidence angle to below 45° (to enhance diffuse reflection).
Choose devices operating at wavelengths of 905nm or 1550nm (for better penetration).
3. Special Scenario Strategies
① Dynamic Target Measurement (e.g., moving vehicles):
- Prioritize vehicle license plates (high reflectivity areas) or light-colored car bodies.
- Use multiple echo recognition technology (to filter out rain and fog interference).
② Complex Surface Treatment:
- For dark-colored metal, apply matte coatings (which can improve reflectivity to 30%).
- Install polarizing filters in front of glass curtain walls (to suppress specular reflection).
③ Environmental Interference Compensation:
- Enable background light suppression algorithms in bright light conditions.
- In rain or snow, use pulse interval modulation (PIM) technology.
4. Equipment Parameter Tuning Guidelines
- Power Adjustment: Increase the laser power for low-reflectivity targets (ensure compliance with eye safety limits).
- Receiving Aperture: Increase the diameter of the receiving lens (for every doubling, the signal gain increases fourfold).
- Threshold Setting: Dynamically adjust the signal trigger threshold (to avoid false triggering due to noise).
5. Future Trends: Intelligent Reflectivity Compensation Technology
Next-generation distance measurement systems are beginning to integrate:
- Adaptive Gain Control (AGC): Real-time adjustment of the photodetector sensitivity.
- Material Recognition AI Algorithms: Matching material types using echo waveform features.
- Multispectral Fusion: Combining visible light and infrared data for more comprehensive judgment.
Conclusion
Mastering the characteristics of reflectivity is a core skill for improving measurement accuracy. By scientifically selecting targets and configuring devices properly, even in ultra-low reflectivity scenarios (below 10%), millimeter-level measurement accuracy can be achieved. As intelligent compensation technologies develop, future measurement systems will adapt more “smartly” to complex environments. However, understanding the basic principles of reflectivity will always be an essential skill for engineers.
Post time: Mar-04-2025