Biomedical subjects

Zhaoyan Liu

Publications and source records attributed to Zhaoyan Liu.

4 recordsLinked to original sources

PubMed2006

Estimating random errors due to shot noise in backscatter lidar observations.

We discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson- distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root mean square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF, uncertainties can be reliably calculated from or for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar and tested using data from the Lidar In-space Technology Experiment.

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PubMed2006

Simple relation between lidar multiple scattering and depolarization for water clouds.

An empirical relationship is derived between the multiple-scattering fraction and the linear depolarization ratio by using Monte Carlo simulations of water clouds measured by backscatter lidar. This relationship is shown to hold for clouds having a wide range of extinction coefficients, mean droplet sizes, and droplet size distribution widths. The relationship is also shown to persist for various instrument fields of view and for measurements made within broken cloud fields. The results obtained from the Monte Carlo simulations are verified by using multiple-field-of-view lidar measurements. For space-based lidars equipped to measure linear depolarization ratios, this new relationship can be used to accurately assess signal perturbations due to multiple scattering within nonprecipitating water clouds.

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PubMed2002

Extinction-to-backscatter ratio of Asian dust observed with high-spectral-resolution lidar and Raman lidar.

Extinction-to-backscatter ratio or lidar ratio is a key parameter in the issue of backscatter-lidar inversions. The lidar ratio of Asian dust was observed with a high-spectral-resolution lidar and a combined Raman elastic-backscatter lidar during the springs of 1998 and 1999. The measured values range from 42 to55 sr in most cases, with a mean of 51 sr. These values are significantly larger than those predicted by the Mie computations that incorporate measured Asian dust size distributions and a range of refractive index with a typical value of 1.55-0.005i. The enhancement of lidar ratio is mostly due to the nonsphericity of dust particles, as indicated by the T-matrix calculations for spheroid particles and a number of other theoretical studies. In addition, possible contamination of urban aerosols may also contribute somewhat in optically thin cases. Mie theory, although it can well describe spherical particle scattering, will not be sufficient to represent the scattering characteristics of irregular particles such as Asian dust, especially in directions larger than approximately 90 degrees when the size parameter is large.

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PubMed2002

Simulation study for cloud detection with space lidars by use of analog detection photomultiplier tubes.

Output signal electrons from photomultiplier tubes (PMTs) have neither a Gaussian nor a Poisson distribution because of changes induced by multiplication when the number of input signal photons and dark electrons is fewer than approximately 100. Therefore the assumption of a Gaussian distribution of signal electrons cannot be used in simulations for space lidar observations with PMTs, for which the number of return signal photons is normally small. A theory is introduced for analog detection with PMTs that have Poisson-distributed secondary-electron emission at each dynode stage. The theory is validated by straightforward numerical simulations. It is shown that the multiplication in PMTs is a multiply stochastic Poisson process and that the distribution of output signal electrons can be interpreted basically as Neyman type A. Analysis by the threshold method of cloud detection with a space lidar shows considerable difference between a Gaussian approximation and the exact distribution. The result indicates that the threshold level must be optimized for the exact distribution. Return signals were simulated for a proposed space lidar, and cloud detection with the threshold method was demonstrated.

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