风云三号B星微波成像仪资料在陆地上的无线电频率干扰信号的识别

Detection of Radio-Frequency Interference Signal over Land from FY-3B Microwave Radiation Imager (MWRI)

  • 摘要: 风云三号B星(FY-3B)搭载的微波成像仪(MWRI)包括5个频率(10.65,18.7,23.8,36.5,89.0GHz),每个频率都有垂直极化和水平极化两个通道。研究发现,MWRI资料在陆地上有无线电频率干扰(RFI)现象,这些干扰信号通常可以用谱差法和主分量分析法(PCA)进行识别。主分量分析法是利用自然辐射的观测具有全通道相关性的特征,能够从自然辐射中识别出无线电频率干扰信号。在投影到第一主成分上的高值区,通常存在无线电频率干扰。然而,谱差法和主分量分析法都不能可靠地识别出在冰雪覆盖面和有散射效应的地表上的干扰信号,因为在这些区域10.65和18.7GHz通道之间的亮温差也有大的正值。因此,利用标准化的主分量分析法来改进对无线电频率干扰的识别和探测。新的识别方法目前能够有效地应用于微波成像仪资料中干扰信号的识别。微波成像仪资料在10.65GHz频率上的无线电频率干扰信号广泛分布在欧洲和日本,但在中国和美国较少出现。

     

    Abstract: The MicroWave Radiation Imager (MWRI) onboard the FengYun (FY)-3B satellite has fi ve frequencies at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz, each having dual channels at vertical and horizontal polarization states, respectively. It is found that radiofrequency interference (RFI) is present in MWRI data over land. The RFI signals are, in general, detectable from a spectral difference method and a principal component analysis (PCA) method. In particular, the PCA method is applied to derive RFI signals from natural radiations by using the characteristics of natural radiation measurements having all-channel correlations. In the area where data have a higher projection onto the fi rst principle component (PC) mode, RFI is, in general, present. However, both the spectral and PCA methods cannot detect RFI reliably over frozen grounds and scattering surfaces, where the brightness temperature difference between 10.65 and 18.7 GHz is large. Thus, detection is improved through the use of normalized PCA. The new RFI detection algorithm is now working reliably for MWRI applications. It is found that RFI at 10.65 GHz distributes widely over Europe and Japan, and is less popular over the United States and China.

     

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