Biomedical subjects

Vladimir A Kovalev

Publications and source records attributed to Vladimir A Kovalev.

7 recordsLinked to original sources

PubMed2006

Determination of slope in lidar data using a duplicate of the inverted function.

An iterative method for determining slope in noisy lidar data is considered based on the use of a corrected ('shaped') inverted function and an assumed behavior of the unknown function of interest (an 'image function'). The method is utilized for extracting extinction- coefficient profiles from data of multiangle measurements. The sequence and specifics of the retrieval procedure, results of simulations, and essentials of the practical retrieval of particulate extinction-coefficient profiles from signals of the elastic scanning lidar are considered. The methodology may be applicable when extracting the extinction-coefficient profiles from an elastic lidar operating in a multiangle scanning mode, a combined Raman elastic-backscatter lidar, or a high spectral resolution lidar operating in a fixed angular position.

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PubMed2005

Simple algorithm to determine the near-edge smoke boundaries with scanning lidar.

We propose a modified algorithm for the gradient method to determine the near-edge smoke plume boundaries using backscatter signals of a scanning lidar. The running derivative of the ratio of the signal standard deviation (STD) to the accumulated sum of the STD is calculated, and the location of the global maximum of this function is found. No empirical criteria are required to determine smoke boundaries; thus the algorithm can be used without a priori selection of threshold values. The modified gradient method is not sensitive to the signal random noise at the far end of the lidar measurement range. Experimental data obtained with the Fire Sciences Laboratory lidar during routine prescribed fires in Montana were used to test the algorithm. Analysis results are presented that demonstrate the robustness of this algorithm.

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PubMed2004

Distortions of the extinction coefficient profile caused by systematic errors in lidar data.

The influence of lidar data systematic errors on the retrieved particulate extinction coefficient profile in clear atmospheres is investigated. Particularly, two sources of the extinction coefficient profile distortions are analyzed: (1) a zero-line offset remaining after subtraction of an inaccurately determined signal background component and (2) a far-end incomplete overlap due to poor adjustment of the lidar system optics. Inversion results for simulated lidar signals, obtained with the near- and far-end solutions, are presented that show advantages of the near-end solution for clear atmospheres.

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PubMed2004

Calibration method for multiangle lidar measurements.

A new method based on a two-angle approach is developed to determine the lidar solution constant from scanning elastic lidar data, hence providing a relative calibration for each lidar scan. Once the solution constant is determined, the vertical profiles of atmospheric extinction can be calculated. With this calibration method a minimization technique is used that replaces the linear regression used in a known two-angle approach that requires only local atmospheric homogeneity over a restricted altitude calibration range rather than overall horizontal homogeneity. Lidar signals from at least one pair of elevation angles are used, averaged in time when the system is operated in a permanent two-angle mode, or an arbitrary number of signal pairs is used, when a two-dimensional lidar scan is being processed. The method is tested extensively with synthetic data. The calibration method is a robust tool for determining the solution constant to the lidar equation and for obtaining vertical profiles of atmospheric extinction.

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PubMed2003

Near-end solution for lidar signals that includes a multiple-scattering component.

A variant of the near-end solution is presented that allows one to consider a multiple-scattering component in lidar measurements of distant clouds or dense smoke. It is assumed that the lidar signal, contaminated by multiple scattering, obeys a single-scattering lidar equation in which an additional term, which is related to the range-dependent ratio of a multiple-to-single-scattering component, is included. For the inversion, a brink solution is proposed that does not require an a priori selection of the extinction-to-backscatter ratio in the optically dense aerosol formation under investigation. The solution requires either knowledge of the multiple-to-single-scattering ratio (e.g., determined experimentally with a multiangle lidar) or the use of the analytical dependence of the multiple-to-single-scattering ratio on the aerosol optical depth. In the latter case, an iterative technique is used.

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PubMed2003

Stable near-end solution of the lidar equation for clear atmospheres.

A stable variant of the near-end solution has been developed for inversion of lidar signals measured in clear atmospheres. The inversion is based on the use of reference values of the extinction coefficient obtained with a nephelometer at the lidar measurement site. The inversion method, based on a combination of the optical depth and boundary point solutions, is illustrated by simulated and experimental data.

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PubMed2002

Analytical differentiation of the differential-absorption-lidar data distorted by noise.

A method of analytical differentiation is developed for processing differential absorption lidar (DIAL) data. The method is based on simple analytical transformation of the DIAL on and off signal ratio. The derivatives consequently are found for either individual data points or local zones of the measurement range. The method makes possible the separation of local zones of interest and the separate investigation of these. The smoothing level is established by the selected value of the exponent in a transformation formula rather than by the selection of the resolution range. The method does not require the calculation of local signal increments. This reduces significantly the high-frequency noise in the measured concentration. The method is general and can be used for different experimental data, including inelastic (Raman) lidar data. The processing technique is practical and does not require a determination of the solution for a large set of algebraic equations. It is based on the simple repetition of the same type of calculations with different constants. The method can easily be implemented for practical computations.

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