A semi-automated procedure for the emitter–receiver geometry characterization of motor-controlled lidars

Abstract

Abstract. To correctly understand and interpret lidar-acquired signals and to provide high-quality data, the characterization of the lidar transmitter–receiver geometry is required. For example, being fundamental to correctly align lidar systems, this characterization is useful to improve the efficiency of the alignment procedure. In addition, some applications (e.g. air quality monitoring) need to quantitatively interpret the observations even in the range where the overlap between the telescope field of view and the laser beam is incomplete. This is generally accomplished by correcting for the overlap function. Within the frame of lidar-based networks (e.g. ACTRIS/EARLINET, the Aerosol, Clouds and Trace Gases Research Infrastructure/European Aerosol Research Lidar Network), there is a need to define standardized approaches to deal with lidar geometry issues. The multi-wavelength multi-telescope Rayleigh–Mie–Raman “9-eyes” system in Rome Tor Vergata, part of ACTRIS/EARLINET, has the capability, through computer-controlled servomotors, to change the orientation of the laser beams and the 3D position of the diaphragm of the receiving optical system around the focal point of the telescopes. Taking advantage of these instrumental design characteristics an original approach to characterize the dependency of the acquired signal from the system relative transmitter–receiver geometry (the mapping procedure) was developed. The procedure consists in a set of programs controlling both the signal acquisition as well as the motor movements. The approach includes solutions to account for atmospheric and laser power variability likely to occur during the mapping sessions. The paper describes in detail the developed procedure and applications such as the optimization of the telescope/beam alignment and the estimation of the overlap function. The results of the mapping applied to a single combination of telescope-laser beam are shown and discussed. The effectiveness of the mapping-based alignment was successfully verified by comparing the whole signal profile and the outcome of the telecover test, adopted in EARLINET, for a manual and a mapping-based alignment. A significant signal increase and lowering of the full overlap height (from 1500 m to less than 1000 m) was found. The overlap function was estimated down to 200 m and compared against the one obtained from a geometric model. The developed procedure also allowed estimating the absolute and relative tilt of the laser beam. The mapping approach, even in simplified versions, can be adapted to other lidars to characterize and align systems with non-motorized receiving geometry.