Methodology of dimensionless multiplicative decomposition for atmospheric lidar evaluation

Ravil Agishev; Barry Gross; Adolfo Comeron

doi:10.1117/12.683886

3 October 2006 Methodology of dimensionless multiplicative decomposition for atmospheric lidar evaluation

Ravil Agishev, Barry Gross, Adolfo Comeron

Proceedings Volume 6367, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II; 63670R (2006) https://doi.org/10.1117/12.683886
Event: SPIE Remote Sensing, 2006, Stockholm, Sweden

Abstract

In the present paper, we show application examples of united generalized methodology for atmospheric lidar assessment, which uses the dimensionless-parameterization as a core component. It is based on a series of our previous works where the problem of universal parameterization over many lidar technologies were described and analyzed from different points of view. A methodology of spatial-angular filtering efficiency was used for comparison of different receiving system designs on the criterion of stability against background radiation. The dimensionless parameterization concept applied to photodetectors of remote sensing instruments allowed predicting the lidar receiver performance in presence of sky background. The approach can be widely used to evaluate a broad range of lidar system capabilities for a variety of lidar remote sensing applications, as well as to serve as a basis for selection of appropriate lidar system parameters for a specific application. Such a methodology provides generalized, uniform and objective approach for the evaluation of a broad range of lidar types and systems (aerosol, Raman, DIAL), operating on different targets (backscatter or topographic) and under intense sky background conditions, and can be used within the lidar community to compare different lidar instruments.

Citation Download Citation

Ravil Agishev, Barry Gross, and Adolfo Comeron "Methodology of dimensionless multiplicative decomposition for atmospheric lidar evaluation", Proc. SPIE 6367, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II, 63670R (3 October 2006); https://doi.org/10.1117/12.683886

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