An Instrumental Basis for Multispectral Lidar With Spectrally-Resolved Distance Measurements

Abstract

Commission II, WG II/3 KEY WORDS: Hyperspectral and multispectral LiDAR, reflectorless distance measurement, remote material probing, laser scanning, femtosecond laser ABSTRACT:Hyperspectral solutions augment laser scanning technology with material probing capabilities by measuring target reflectance along with topography. We propose a novel instrumental basis that enables also spectrally-resolved distance measurement with sufficient sensitivity as to access dispersive phenomena on the reflecting target and along the propagation medium, further enhancing the material analysis capabilities of hyperspectral approaches. To this end we have extended distance metrology using intermode beat notes of a mode-locked femtosecond laser to cover flexibly selected spectral regions. The approach is based on an ultra-broadband source derived from a femtosecond laser via coherent supercontinuum generation. Herein we provide a first demonstration of the successful application of this technique to reflectorless measurements and thus its feasibility for multispectral LiDAR. We use a table-top experimental set-up to assess the approach by measuring distance, spectrally-resolved relative distance and reflectance to 5 different material samples on 5 multiplexed contiguous spectral bands of 50 nm in the range of 600 nm to 850 nm. We have achieved a distance measurement precision and accuracy better than 100 µm using integration times of about 30 ms, with promising perspectives regarding scalability to practical distances. The spectrally-resolved distance measurements also show repeatable material-dependent profiles with differences between materials up to several tenths of mm in some spectral bands. Combined with simultaneously acquired reflectance estimations, these profiles enable collecting additional target information, indicating the potential of the approach to enhance the material probing capabilities of prospective multispectral laser scanners.

Classification of material and surface roughness using polarimetric multispectral LiDAR

“…The distance of the target is calculated from the phase difference of the electric beat notes output by the two APDs. 21 According to the radar equation, 22,23 the reflectance R of a target can be expressed by a function of the received optical power P r and the transmitted optical power P t of the LiDAR system as R = K • P r /P t . The coefficient K depends on the measurement geometry (mainly incidence angle and ranging distance), atmospheric attenuation, and several system constants (e.g., aperture of the collection optics, responsivity of the optical detector).…”

Classification of material and surface roughness using polarimetric multispectral LiDAR

“…The distance of the target is calculated from the phase difference of the electrical beat notes output by the two APDs. 48 Forty band-pass filters mounted in eight filter wheels provide two different spectral configurations (Fig. 2) within the spectral range of the SC-OFC.…”

“…The other portion of the filtered laser beam is focused on the reference APD. The distance of the target is calculated from the phase difference of the electrical beat notes output by the two APDs 48 . Forty band-pass filters mounted in eight filter wheels provide two different spectral configurations (Fig.…”

Polarimetric femtosecond-laser LiDAR for multispectral material probing

“…13 A novel approach to multispectral LiDAR based on a femtosecond laser supercontinuum has been proposed in the past, providing both spectrally-resolved phase and power observations of the optical signals backreflected from natural targets. 14 These observations enable deriving distance and reflectance spectral signatures defined by the target material. This work showed that the distance spectral signature complements the reflectance information, thus both signatures can jointly enhance material classification compared with standard multispectral approaches.…”