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Standoff lidar simulation for biological warfare agent detection, tracking and classification

机译:用于生物战剂检测,跟踪和分类的对峙激光雷达模拟

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Lidar has been identified as a promising sensor for remote detection of biological warfare agents (BWA). Elastic IR lidar can be used for cloud detection at long ranges and UV laser induced fluorescence can be used for discrimination of BWA against naturally occurring aerosols. This paper will describe a simulation tool which enables the simulation of lidar for detection, tracking and classification of aerosol clouds. The cloud model was available from another project and has been integrated into the model. It takes into account the type of aerosol, type of release (plume or puff), amounts of BWA, winds, height above the ground and terrain roughness.rnThe model input includes laser and receiver parameters for both the IR and UV channels as well as the optical parameters of the background, cloud and atmosphere. The wind and cloud conditions and terrain roughness are specified for the cloud simulation. The search area including the angular sampling resolution together with the IR laser pulse repetition frequency defines the search conditions. After cloud detection in the elastic mode, the cloud can be tracked using appropriate algorithms. In the tracking mode the classification using fluorescence spectral emission is simulated and tested using correlation against known spectra. Other methods for classification based on elastic backscatter are also discussed as well as the determination of particle concentration. The simulation estimates and displays the lidar response, cloud concentration as well as the goodness of fit for the classification using fluorescence.
机译:激光雷达已被认为是用于远程检测生物战剂(BWA)的有前途的传感器。弹性红外激光雷达可用于远距离云探测,而紫外线激光诱导的荧光可用于区分BWA与天然气溶胶。本文将介绍一种仿真工具,该工具可以对激光雷达进行仿真,以检测,跟踪和分类气溶胶云。该云模型可从另一个项目获得,并已集成到该模型中。它考虑了气溶胶的类型,释放的类型(泡沫或粉扑),BWA的量,风,地面上的高度和地形的粗糙度.rn模型输入包括用于IR和UV通道的激光和接收器参数以及背景,云和大气的光学参数。为云模拟指定了风云条件和地形粗糙度。包括角度采样分辨率和IR激光脉冲重复频率的搜索区域定义了搜索条件。在弹性模式下检测到云之后,可以使用适当的算法跟踪云。在跟踪模式下,将模拟使用荧光光谱发射的分类,并使用与已知光谱的相关性进行测试。还讨论了基于弹性反向散射的其他分类方法以及颗粒浓度的确定。该模拟估算并显示激光雷达响应,云浓度以及使用荧光进行分类的拟合优度。

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