项目名称: 基于综合孔径的地球静止轨道气象卫星毫米波大气探测载荷理论与关键技术研究
项目编号: No.41275032
项目类型: 面上项目
立项/批准年度: 2013
项目学科: 天文学、地球科学
项目作者: 陈柯
作者单位: 华中科技大学
项目金额: 80万元
中文摘要: 对突发性气象灾害的及时预测需要在地球静止轨道气象卫星上实现高分辨率的毫米波大气探测载荷,受空间分辨率限制该领域的应用还是世界空白。实孔径辐射计受卫星平台限制难以实现大孔径毫米波扫描天线,采用稀疏天线阵列的综合孔径辐射计被提出作为一种极有希望解决地球静止轨道毫米波大气探测的技术手段,是国际研究的热点之一。由于其高复杂度,在阵列规模、误差校正、图像反演、定标方面还存在技术瓶颈和待解决的关键科学问题,限制了综合孔径技术在该领域的应用发展。 本项目面向我国下一代地球静止轨道气象卫星"风云四号"对微波大气探测载荷的应用需求,提出并系统研究空间频域稀疏采样阵列优化理论、多源联合外校正及旋转冗余空间校正理论、贝叶斯统计反演方法、天体源外定标等新理论新方法来解决综合孔径载荷在地球静止轨道微波大气探测中的瓶颈技术和关键科学问题,为我国地球静止轨道微波遥感载荷技术的发展提供新思路、新方法和关键技术支撑。
中文关键词: 地球静止轨道气象卫星;大气探测;综合孔径辐射计;误差校正;图像反演算法
英文摘要: It is necessary to achieve the high spatial resolution millimeter-wave atmospheric sounding load in the geostationary orbit weather satellite for the timely prediction of unexpected meteorological disasters, but the application field is still world blank for the spatial resolution limitation. It is difficult to achieve large-aperture millimeter-wave scanning antenna in spaceborne real aperture radiometer due to the satellite platform restrictions, so aperture synthesis radiometer based on sparse antenna array is proposed as a very promising techniques to achieve geostationary microwave atmospheric sounding, which is one of the hot spots of the international research. Due to its high complexity, there are several technical bottlenecks and key scientific issues to be resolved in the array size, system error calibration, image inversion and absolute calibration, which limit the development of synthetic aperture technology in the field. This project proposes some new theory and new methods such as the space frequency-domain sparse sampling array optimization theory, the multi-source joint external calibration and array rotation redundancy space calibration theory, Bayesian statistical inversion, celestial source absolute calibration to solve bottleneck technologies and key scientific issues of aperture synthesis lo
英文关键词: geostationary orbit meteorological satellite;atmospheric sounding;Aperture Synthesis Radiometer;error calibration;image inversion algorithm