Guan Li, Xia Shichang, Zhang Sibo. Identifying the interference of spaceborne microwave radiometer over large water area. J Appl Meteor Sci, 2015, 26(1): 22-31. DOI:  10.11898/1001-7313.20150103.
Citation: Guan Li, Xia Shichang, Zhang Sibo. Identifying the interference of spaceborne microwave radiometer over large water area. J Appl Meteor Sci, 2015, 26(1): 22-31. DOI:  10.11898/1001-7313.20150103.

Identifying the Interference of Spaceborne Microwave Radiometer over Large Water Area

DOI: 10.11898/1001-7313.20150103
  • Received Date: 2014-04-02
  • Rev Recd Date: 2014-09-17
  • Publish Date: 2015-01-31
  • The phenomenon of satellite-measured passive microwave thermal emission from natural surface and atmosphere being mixed with signals from active sensors is referred as radio-frequency interference (RFI). Due to increasing conflicts between scientific and commercial users of the radio spectrum, RFI is an increasing serious problem for microwave active and passive remote sensing. RFI greatly affects the quality of data and retrieval products from space-borne microwave radiometry, as the C-band and X-band of spaceborne microwave radiometer operate in unprotected frequency bands. Interference signals over land come dominantly from lower frequency active microwave transmitters, including radar, air traffic control, cell phone, garage door remote control, GPS signal on highway, defense tracking and vehicle speed detection for law enforcement. The signal emanating from geostationary communication and television satellites that reflect off the ocean surface is the major interference source over ocean of spaceborne passive microwave imagers. RFI detection and correction of low-frequency radiances over large water area is extremely important before these data being used for either geophysical retrievals or data assimilation in numerical weather prediction models.RFI over ocean and inland large water area of North America, as well as over the coastline of China are identified and analyzed based on Advanced Microwave Scanning Radiometer (AMSR-E) observations using double principal component analysis (DPCA) algorithm. The AMSR-E instrument is primarily designed to enhance cloud and surface sensing capabilities. The DPCA method takes advantage of the multi-channel correlation for natural surface radiations, as well as the de-correlation between different RFI contaminated frequencies. Results show that the DPCA method works well in detecting the location and intensity of RFI over ocean and large water area. The AMSR-E observation over the ocean of America at 18.7 GHz is mainly interfered by geostationary television satellites DirecTV. The RFI location and intensity from the ocean reflection of downlink radiation highly depends upon the relative geometry between the geostationary satellite and the measuring passive sensor. Only the field of views with smaller glint angle (defined as the angle between the geostationary specular reflection vector and the AMSR-E line-of-sight vector) is easily affected by RFI. The stronger RFI distribute near the Great Lakes of America, and the RFI magnitude of East and West Coast is stronger than south coast. AMSR-E observations of 6.925 GHz are contaminated by RFI along the coastline of China, while observations of 18.7 GHz are not affected.
  • Fig. 1  The first PC coefficient u1 and the geostationary satellite gilint angle θ of AMSR-E 18.7 GHz with horizontal polarization of decending node in June 2011

    Fig. 2  The sketch map of the reflected geostationary TV satellite downlink signals by ocean surface and the definition of glint angle θ

    Fig. 3  The average glint angle θ based on AMSR-E decending observations from 1 June to 16 June in 2011

    Fig. 4  The synthesized distribution of first PC coefficient u1 based on AMSR-E 18.7 GHz decending observations with horizontal polarization from 1 June to 16 June in 2011

    Fig. 5  The monthly average RFI intensity at 18.7 GHz horizontal polarization over America ocean from 1 June to 2 July in 2011

    Fig. 6  The first PC coefficient u1 of AMSR-E 18.7 GHz with horizontal polarization of acending node on 4 June (a) and 7 June (b) in 2011

    Fig. 7  The identified RFI along China east coast of AMSR-E 6.9 GHz (a) and 18.7 GHz (b) horizontal polarization on 8 June 2011

    Fig. 8  The brightness temperature (a) and the RFI (b) of FY-3 MWRI 18.7 GHz horiontal polarization on 8 June 2011

    Table  1  AMSR-E instrument description

    通道 中心频率/GHz 极化方式 带宽/MHz 空间分辨率 灵敏度/K
    1 6.925 水平 350 74 km×43 km 0.3
    2 6.925 垂直 350 74 km×43 km 0.3
    3 10.65 水平 100 51 km×30 km 0.6
    4 10.65 垂直 100 51 km×30 km 0.6
    5 18.7 水平 200 27 km×16 km 0.6
    6 18.7 垂直 200 27 km×16 km 0.6
    7 23.8 水平 400 31 km×18 km 0.6
    8 23.8 垂直 400 31 km×18 km 0.6
    9 36.5 水平 1000 14 km×8 km 0.6
    10 36.5 垂直 1000 14 km×8 km 0.6
    11 89 水平 3000 6 km×4 km 1.1
    12 89 垂直 3000 6 km×4 km 1.1
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    Table  2  Major geostationary TV satellite

    卫星名称 经度 覆盖区域 频率/GHz
    DirecTV 10 103°W 美国 18.8~19.3
    DirectV 11 99°W 美国 18.3~18.8
    Hot Bird 13°E 欧洲 10.7~12.75
    Atlantic Bird 7°W 欧洲 10.7~11.7
    Astra 19.2°E 欧洲 10.7~10.95
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    Table  3  The percentage of glint angle θ in different range at RFI area (unit:%)

    日期 0°≤θ < 5° 5°≤θ < 15° θ≥15°
    2011-06-01 28.59 71.41 0
    2011-06-04 38.21 50.81 10.98
    2011-06-07 11.42 78.53 10.05
    2011-06-11 55.27 44.13 0.6
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    • Received : 2014-04-02
    • Accepted : 2014-09-17
    • Published : 2015-01-31

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