FY-3B微波成像仪海洋数据无线电干扰识别  

Identification of radio-frequency interference signal from FY-3B microwave radiation imager over ocean

作　　者：冯呈呈[1] 赵虹[1] 

机构地区：[1]南京信息工程大学资料同化研究与应用中心,江苏南京210044

出　　处：《遥感学报》2015年第3期465-475,共11页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家重点基础研究发展计划(973计划)(编号:2010CB951600);公益性行业(气象)科研专项(编号:GYHY201406008);江苏省普通高校研究生科研创新计划(编号:CXLX13_483;CXZZ13_0503);江苏高校优势学科建设工程资助项目(编号:PAPD)

摘　　要：中国风云3号B星(FY-3B)上的微波成像仪MWRI通过5个频率(10.65 GHz,18.7 GHz,23.8 GHz,36.5 GHz和89.0 GHz)的双极化通道对地球表面进行监测。研究表明,MWRI资料的低频波段数据中存在着无线电频率干扰(RFI)现象,这些污染信号对遥感数据和反演产品质量产生极大的影响。本文尝试使用多通道回归方法和双主成分分析(DPCA)方法识别MWRI的10.65 GHz水平通道亮温海洋区域中的RFI信号。结果表明,双主成分分析法可以有效地识别出海洋上的RFI信号。微波成像仪10.65 GHz水平通道亮温数据中的RFI信号主要分布在地中海等欧洲附近海域,也存在于美国、日本、澳大利亚等近岸地区。Radio-Frequency Interference（ RFI） is an increasingly severe problem for present and future microwave satellite missions. It causes serious problems to passive and active microwave sensing observations and to corresponding retrieval products.Detecting RFI signals is an important step before data can be used. The Microwave Radiation Image（ MWRI） on board the Feng Yun（ FY）-3B satellite can provide the brightness temperature data at 10. 65 GHz,18. 7 GHz,23. 8 GHz,36. 5 GHz,and89 GHz,each having dual channels at horizontal and vertical polarization states. RFI signals are present in MWRI data over land and ocean. RFI signals from data over ocean are more difficult to detect than those over land because of the low microwave emissivity of the sea surface. In general,RFI signals are detectable by using a multichannel regression method and retrieval chi-square probability. However,the two methods need auxiliary brightness temperature data within a certain period of time under conditions without ice and RFI,and located away from the coast. In this study,we use multichannel regression and Double Principal Component Analysis（ DPCA） to identify the RFI signals from MWRI data over ocean. DPCA takes advantage of the decorrelation for RFI signals and the correlation characteristics of radiation data in different channels for nature surface,including snow cover and synoptic process. This method does not need auxiliary brightness temperature data,and it can been used to offer a real-time RFI detection method before data are provided. Compared with the results of multichannel regression,the results of DPCA can be considered effective in detecting RFI signals from MWRI ocean brightness temperatures. Moreover,the results obtained from the water near North America in winter indicate that multichannel regression produces false results over sea ice. The false signals could be avoided effectively in DPCA. The consistent results from different methods show that the RFI signals detected are credible. The RFI signals of MWR

关 键 词：微波遥感 微波成像仪MWRI 无线电频率干扰RFI 双主成分分析DPCA 

分 类 号：P715.6[天文地球—海洋科学]