Reduced Image Aliasing With Microwave Radiometers and Weather Radar Through Windowed Spatial Averaging
Reduced Image Aliasing With Microwave Radiometers and Weather Radar Through Windowed Spatial Averaging
复制标题
微波辐射计和气象雷达通过窗口空间平均减少图像混叠
DOI：
10.1109/tgrs.2015.2445100
复制
发表时间：
2015
影响因子：
8.2
通讯作者：
Lihua Li
中科院分区：
文献类型：
--
作者：
M. McLinden;Edward J. Wollack;G. Heymsfield;Lihua Li
微波遥感仪器检测和图像物理现象，例如亮度温度和体积反射率。这些测量值的空间分辨率受仪器的物理特性的限制，例如天线大小，空间扫描模式和时间采样。分析表明，常见的采样方案未列出天线上存在的空间信息。在这里，我们解决了通过将Nyquist Shannon采样理论应用于遥感数据的空间平均和采样，以更好地捕获可用的空间信息。使用重叠的窗口用于空间平均而不是独立治疗像素可以在保持系统敏感性的同时独立改善图像保真度。另外，通过将窗口形状与天线图案匹配，可以最大化对空间小目标的敏感性。解决了扫描辐射仪，雷达和梯级阵列系统的空间成像。这些原则通过国家航空和太空管理局的理论和数据来证明，戈达德太空飞行中心的高空成像风和雨水降雨探测器（HIWRAP）雷达。
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.