基于GPU的阵列气象雷达高分辨率强场融合

Kai Ye, Ling Yang, Shuqing Ma, Xiaoqiong Zhen
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引用次数: 0

摘要

阵列气象雷达(AWR)是一种新型气象雷达。AWR采用了分布式相控阵技术。AWR提供了非常高的时空分辨率,可以获得高变化速度的小尺度天气系统。AWR系统从至少三个雷达前端提供对同一目标的联网和协调观测。介绍了一种基于图形处理器(GPU)的快速高分辨率光强场融合算法。利用CPU和GPU之间异步执行的特点,在CUDA上对融合算法进行并行化和优化。首先,基于AWR前端体扫描的强度数据,在每个GPU线程中计算方位角和高程的分辨率扩展系数;然后,垂直和水平填充同时完成。最后,在通用坐标系下实现了三个前端强度数据的融合。整个过程已在NVIDIA GPU架构上实现。结果表明,基于gpu的AWR计算方法比传统的基于cpu的AWR计算方法大大提高了计算速度,能够满足气象应用的实时要求。
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High-Resolution Intensity Field Fusion of Array Weather Radar on GPU
Array Weather Radar (AWR) is a new type weather radar. A distributed phased array technology is utilized to the AWR. With offering very high spatiotemporal resolution, the AWR can obtain the small-scale weather systems with high changing speed. The AWR system provides networked and coordinated observations of the same target from at least three radar front ends. This paper introduces a fast and high-resolution intensity field fusion algorithm for the AWR based on Graphics Processing Unit (GPU). By utilizing the feature of asynchronous execution between CPU and GPU, the fusion algorithm is parallelized and optimized on Compute Unified Device Architecture (CUDA). First, based on the intensity data from the AWR front end volume scans, resolution expansion coefficients in azimuths and elevations are calculated in each GPU thread. Then, the vertical and horizontal filling is completed simultaneously. Finally, the fusion of three front end intensity data is achieved in a common coordinate system. The entire process has been implemented on NVIDIA GPU architecture. The result shows that the GPU-based method for the AWR greatly improves the speed of calculation compared with the conventional CPUbased implementation, which can satisfy the requirements of meteorological applications in real-time.
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