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Diffusion patterns of a pulsed laser beam seen by a monostatic and a bistatic CCD lidar

机译:单基地和双基地CCD激光雷达观察到的脉冲激光束的扩散模式

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The transport of light through the atmosphere is modeled as a Levy-type Markovian jump process of stochastic corpuscular multiple scattering of photons including polarization. The backward Kolmogorov differential equation of this Markovian jump process is the general radiative transfer equation with polarization. Based on this stochastic multiple scattering process, Monte Carlo codes have been designed to calculate lidar returns containing essential contributions of multiple scattering (dense clouds, space). Since the retrieval of micro-physical cloud parameters is an ill-posed problem, it is necessary to collect as much additional information about the cloud as possible. Such information can be obtained by using multiple field of view lidars or CCD lidars. Based on the stochastic multiple scattering process, a new Monte Carlo code has been designed allowing for the calculation of the off-axis diffusion patterns of the emitted pulsed laser beam as it is "seen from the monostatic or bistatic CCD receiver". These patterns allow for the classification of different types of scattering particles. Some examples of such patterns will be shown for clouds of radiative fog and of collections of randomly oriented oblate and prolate cylinders and spheroids. These patterns allow for a simple classification of clouds.
机译:通过大气的光传输被模型化为Levy型马尔可夫跳跃过程,该过程是光子随机小体多次散射(包括极化)的过程。该马尔可夫跳跃过程的后向Kolmogorov微分方程是带极化的一般辐射传递方程。基于这种随机多次散射过程,已设计了蒙特卡洛代码来计算包含多次散射(密集云,空间)的基本贡献的激光雷达返回。由于微物理云参数的检索是一个不适的问题,因此有必要收集有关云的尽可能多的附加信息。这样的信息可以通过使用多个视场激光雷达或CCD激光雷达获得。基于随机多重散射过程,设计了新的蒙特卡洛代码,可以计算“从单静态或双静态CCD接收器看到的”脉冲激光束的轴外扩散模式。这些图案允许对不同类型的散射颗粒进行分类。将针对辐射雾云以及随机定向的扁长形和长圆形圆柱体和椭球形的集合显示此类模式的一些示例。这些模式允许对云进行简单分类。

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