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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >Reduced Image Aliasing With Microwave Radiometers and Weather Radar Through Windowed Spatial Averaging
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Reduced Image Aliasing With Microwave Radiometers and Weather Radar Through Windowed Spatial Averaging

机译：通过窗口空间平均减少微波辐射计和天气雷达的图像混叠

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摘要

Microwave remote sensing instruments detect and image physical phenomena such as brightness temperature and volume reflectivity. The spatial resolution of these measurements is limited by the physical properties of the instrument such as the antenna size, the spatial scan pattern, and temporal sampling. Analysis shows that common sampling schemes undersample the spatial information present at the antenna. Here, we address methods to better capture the spatial information available by applying the Nyquist–Shannon sampling theory to the spatial averaging and sampling of remote sensing data. The use of overlapping windows for spatial averaging rather than treating pixels independently improves the image fidelity while maintaining the system sensitivity. Additionally, the sensitivity to spatially small targets can be maximized by matching the window shape to the antenna pattern. The spatial imaging of scanning radiometers, radars, and phased-array systems is addressed. These principles are demonstrated with the theory and data from the National Aeronautics and Space Administration Goddard Space Flight Center's High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) radar.
机译：微波遥感仪器可以检测并成像物理现象，例如亮度温度和体积反射率。这些测量的空间分辨率受到仪器物理特性（例如天线尺寸，空间扫描方向图和时间采样）的限制。分析表明，常见的采样方案对天线上存在的空间信息进行了欠采样。在这里，我们介绍了通过将Nyquist-Shannon采样理论应用于遥感数据的空间平均和采样来更好地捕获可用空间信息的方法。使用重叠窗口进行空间平均而不是独立处理像素可以提高图像保真度，同时保持系统灵敏度。另外，通过将窗口形状与天线方向图匹配，可以最大化对空间较小目标的灵敏度。解决了扫描辐射计，雷达和相控阵系统的空间成像问题。美国国家航空航天局戈达德太空飞行中心的高空成像风雨机载廓线仪（HIWRAP）的理论和数据证明了这些原理。

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