相控阵列天线的各收发通道幅相误差会对其性能产生较大影响。在分析相控阵列天线幅相误差的产生原因的基础上,提出了一种幅相误差外、内校准结合方法,其中外校准方法基于(Multiple Signal Classification,MUSIC)算法引入模拟退火算法对...相控阵列天线的各收发通道幅相误差会对其性能产生较大影响。在分析相控阵列天线幅相误差的产生原因的基础上,提出了一种幅相误差外、内校准结合方法,其中外校准方法基于(Multiple Signal Classification,MUSIC)算法引入模拟退火算法对互耦矩阵和阵元位置扰动进行联合估计,可补偿加工制造安装公差及天线阵元间的互耦导致的幅相误差,内校准方法可补偿天线工作环境变化、器件老化等因素导致的幅相误差。计算机仿真结果表明了方法的有效性。展开更多
Since the launch of its first satellite in 1972, the Landsat program has operated continuously for more than forty years. A large data archive collected by the Landsat program significantly benefits both the academic ...Since the launch of its first satellite in 1972, the Landsat program has operated continuously for more than forty years. A large data archive collected by the Landsat program significantly benefits both the academic community and society. Thermal imagery from Landsat sensors, provided with relatively high spatial resolution, is suitable for monitoring urban thermal environment. Growing use of Landsat data in monitoring urban thermal environment is demonstrated by increasing publications on this subject, especially over the last decade. Urban thermal environment is usually delineated by land surface temperature（LST）. However, the quantitative and accurate estimation of LST from Landsat data is still a challenge, especially for urban areas. This paper will discuss the main challenges for urban LST retrieval, including urban surface emissivity, atmospheric correction, radiometric calibration, and validation. In addition, we will discuss general challenges confronting the continuity of quantitative applications of Landsat observations. These challenges arise mainly from the scan line corrector failure of the Landsat 7 ETM ＋ and channel differences among sensors. Based on these investigations, the concerns are to：（1） show general users the limitation and possible uncertainty of the retrieved urban LST from the single thermal channel of Landsat sensors;（2） emphasize efforts which should be done for the quantitative applications of Landsat data; and（3） understand the potential challenges for the continuity of Landsat observation（i.e., thermal infrared） for global change monitoring, while several climate data record programs being in progress.展开更多
文摘相控阵列天线的各收发通道幅相误差会对其性能产生较大影响。在分析相控阵列天线幅相误差的产生原因的基础上,提出了一种幅相误差外、内校准结合方法,其中外校准方法基于(Multiple Signal Classification,MUSIC)算法引入模拟退火算法对互耦矩阵和阵元位置扰动进行联合估计,可补偿加工制造安装公差及天线阵元间的互耦导致的幅相误差,内校准方法可补偿天线工作环境变化、器件老化等因素导致的幅相误差。计算机仿真结果表明了方法的有效性。
基金supported by the National Key Research Program of China(No.2014CB953900)the National Natural Science Foundation of China(No.41375081)the Sun Yat-sen University“985 Project”Phase 3
文摘Since the launch of its first satellite in 1972, the Landsat program has operated continuously for more than forty years. A large data archive collected by the Landsat program significantly benefits both the academic community and society. Thermal imagery from Landsat sensors, provided with relatively high spatial resolution, is suitable for monitoring urban thermal environment. Growing use of Landsat data in monitoring urban thermal environment is demonstrated by increasing publications on this subject, especially over the last decade. Urban thermal environment is usually delineated by land surface temperature（LST）. However, the quantitative and accurate estimation of LST from Landsat data is still a challenge, especially for urban areas. This paper will discuss the main challenges for urban LST retrieval, including urban surface emissivity, atmospheric correction, radiometric calibration, and validation. In addition, we will discuss general challenges confronting the continuity of quantitative applications of Landsat observations. These challenges arise mainly from the scan line corrector failure of the Landsat 7 ETM ＋ and channel differences among sensors. Based on these investigations, the concerns are to：（1） show general users the limitation and possible uncertainty of the retrieved urban LST from the single thermal channel of Landsat sensors;（2） emphasize efforts which should be done for the quantitative applications of Landsat data; and（3） understand the potential challenges for the continuity of Landsat observation（i.e., thermal infrared） for global change monitoring, while several climate data record programs being in progress.
