...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of the Atmospheric Sciences >A LEAST SQUARES METHOD FOR SPECTRAL ANALYSIS OF SPACE-TIME SERIES
【24h】

A LEAST SQUARES METHOD FOR SPECTRAL ANALYSIS OF SPACE-TIME SERIES

机译：时空序列谱分析的最小二乘法

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Common methods in spectral analyses of satellite data are the discrete Fourier transform (DFT) type of approaches, which generally require regular sampling and uniform spacing. These conditions sometimes cannot be met in the satellite applications, for example, such as one made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). To be able to handle irregular sampling cases, a least squares fitting method is established here for a space-time Fourier analysis and has been applied to the HRDI sampling as well as other regular sampling cases. This method can resolve space-time spectra as robustly and accurately as DFT-type methods for the regular cases. In the same fashion, given an appropriate sampling pattern, it can also handle the irregular cases in which there exist large data gaps, frequent mode changes, and varying weight samples. Various sampling schemes and the associated aliasing spectra are examined. A better sampling plan than those currently used by the UARS instruments to reduce spectral aliasing is proposed, which leads to the question of how to optimize satellite sampling in the future. [References: 19]
机译：卫星数据频谱分析中的常用方法是离散傅里叶变换（DFT）类型的方法，通常需要定期采样和均匀间隔。这些条件有时在卫星应用中无法满足，例如，由高空研究卫星（UARS）上的高分辨率多普勒成像仪（HRDI）产生的条件。为了能够处理不规则采样情况，这里建立了最小二乘拟合方法用于时空傅立叶分析，并且已应用于HRDI采样以及其他常规采样情况。对于常规情况，该方法可以像DFT型方法一样强大而准确地解析时空光谱。以相同的方式，在给定适当的采样模式的情况下，它也可以处理不规则的情况，这些情况存在较大的数据缺口，频繁的模式更改和变化的权重样本。检查了各种采样方案和相关的混叠光谱。提出了一种比UARS仪器目前使用的采样方案更好的采样方案，以减少频谱混叠，这带来了未来如何优化卫星采样的问题。 [参考：19]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号