Supercontinuum-based hyperspectral LiDAR for precision laser scanning.

Area of Science:

• Optics and Photonics
• Remote Sensing
• Spectroscopy

Background:

• Hyperspectral LiDAR combines 3D geometry mapping with spectral reflectance for advanced remote sensing.
• Existing methods offer limited precision for long-range measurements.
• Automated point cloud segmentation is crucial for data analysis.

Purpose of the Study:

• To develop a novel hyperspectral LiDAR system for high-precision 3D surface geometry and spectral reflectance mapping.
• To achieve measurement precision below 0.1 mm at ranges up to 50 m.
• To enable automated material classification within 3D point clouds.

Main Methods:

• Utilized a supercontinuum (SC) laser source coherently broadened from a 780 nm frequency comb.
• Employed differential phase delay monitoring of intermode beat notes for distance measurements.
• Acquired backscattered light spectra using a CCD spectrometer with 0.16 nm resolution.

Main Results:

• Demonstrated measurement precision below 0.1 mm for diffuse targets up to 50 m.
• Achieved relative accuracy on the order of 10^-5 compared to a reference interferometer.
• Showcased initial success in spectrum-based material classification using a linear support vector machine.

Conclusions:

• The proposed hyperspectral LiDAR approach offers significant improvements in precision and accuracy.
• This technology has strong potential for integrated high-precision laser scanning and automated material classification.
• The findings pave the way for more advanced remote sensing and 3D mapping applications.