Cross validations of radio-frequency interference signature in AMSR-E data using two detection methods

基于两种识别方法的AMSR-E资料无线电频率干扰信号的交叉验证（英文）

Radio-frequency interference（RFI） detection for low-frequency microwave measurements is an important step before these data are applied to geophysical parameter retrieval or data assimilation. There are several robust techniques to identify the RFI signals, such as the mean/standard deviation method and the normalized principal component analysis method. However, verification of these existing detection methods remains an open issue in the absence of a reliable validation data-set of the ‘true＇ RFI signals. In this paper, a cross-validation scheme using two independent RFI detection methods is proposed to derive the thresholds for identifying the RFI-contaminated data for the Advanced Microwave Scanning Radiometer for Earth Observing System（AMSR-E）. It is shown that the new scheme is effective in the quantitative classification of the RFI signals in the AMSR-E C-and X-band channels over the continents. Strong RFI signals are found to be populated over cities of the United States at AMSR-E C-band, while RFIs at X-band are mainly observed over Europe and Japan.

卫星微波低频通道的亮温资料广泛存在无线电频率干扰信号,在微波观测应用于反演地球物理参数和资料同化之前,应准确识别出受到频率干扰污染的资料。常用的干扰识别方法包括谱差法、平均值和标准差法以及主分量分析法等,但没有可靠的频率干扰源分布数据集用于评估不同识别方法的准确性。本文提出利用两种独立的干扰识别方法进行交叉验证,获得AMSR-E资料中频率干扰信号的识别阈值。结果表明,该方案能有效识别出AMSR-E资料C波段和X波段通道在陆地上的无线电频率干扰信号。AMSR-E C波段资料在美国人口密集的大城市有较强的干扰信号存在,X波段的干扰信号主要分布在欧洲大陆和日本。