基于多传感器数据融合的微下击暴流感知

Perception of Microburst Based on Multi-Sensor Data Fusion

  • 摘要: 针对微下击暴流的风场特性和几种任务传感器的探测原理,研究基于多传感器数据融合的微下击暴流感知和威胁评估方案.采用扩展卡尔曼滤波的方法建立微下击暴流的解析模型,提出改进的迭代算法实现数据融合并降低参数估计的计算量,依照所建模型进行威胁度评估.仿真实例中选用前视红外(FLIR)和激光雷达(Lidar)探测的风速数据对方案进行验证,并计算F因子,评估其威胁度.

     

    Abstract: According to the wind field characteristics of microburst and the detecting principles of some mission sensors,a scheme for perception and hazard assessment of microburst based on multi-sensor data fusion is proposed.An analytical microburst model is given using extended Kalman filter method,an improved iteration algorithm is presented to fuse data and reduce the amount of computation for parameters estimation,and the hazard of microburst is assessed according to the analytical model.The algorithm is applied to the wind speed data from forward-looking infrared(FLIR) and laser radar (Lidar) to validate the scheme,and F factor is computed to measure hazard.

     

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