| 大面积水体上空星载微波辐射计的干扰识别 |
| |
| 引用本文： | 官莉,夏仕昌,张思勃.大面积水体上空星载微波辐射计的干扰识别[J].应用气象学报,2015,26(1):22-31. |
| |
| 作者姓名： | 官莉 夏仕昌 张思勃 |
| |
| 作者单位： | 1.南京信息工程大学气象灾害预报预警与评估协同创新中心，南京 210044 |
| |
| 基金项目： | 资助项目：江苏省高校自然科学研究重大项目(13KJA170003) |
| |
| 摘 要： | 卫星微波仪器接收的来自地气系统的被动热辐射与主动传感器发射的信号相混合，被称为无线电频率干扰 (RFI)，在主动及被动微波遥感探测领域已成为越来越严重的问题。海洋表面反射的静止通讯、电视卫星下发信号是干扰海洋上星载被动微波辐射计观测的主要来源。该文以先进的微波扫描辐射计AMSR-E为例，采用双主成分分析方法对美国陆地上大面积水体、附近洋面和中国海岸线附近的RFI进行识别，研究表明:美国附近洋面区域星载微波辐射计18.7 GHz通道观测主要受静止电视卫星DirecTV的干扰，由于海表反射引起的RFI非常依赖于静止卫星和星载被动仪器的相对几何位置，只有当闪烁角θ(观测视场镜面反射的静止电视卫星信号方向与视场到星载仪器方向之间的夹角) 较小时卫星观测易受到污染。美国海洋区域较强RFI分布在五大湖区域，离内陆越近RFI越强，东西海岸RFI较强，而整个南海岸干扰相对较弱。中国海岸线附近AMSR-E 6.925 GHz通道观测受RFI影响，而18.7 GHz通道观测未受到干扰。
|
| 关 键 词： | 微波 AMSR-E 无线电频率干扰 (RFI) 识别 |
| 收稿时间： | 4/2/2014 12:00:00 AM |
Identifying the Interference of Spaceborne Microwave Radiometer over Large Water Area |
| |
| Guan Li,Xia Shichang and Zhang Sibo.Identifying the Interference of Spaceborne Microwave Radiometer over Large Water Area[J].Quarterly Journal of Applied Meteorology,2015,26(1):22-31. |
| |
| Authors: | Guan Li Xia Shichang and Zhang Sibo |
| |
| Affiliation: | 1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 2100442.Unit 61741 of PLA, Beijing 100094 |
| |
| Abstract: | 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. |
| |
| Keywords: | microwave AMSR E RFI identification |
|
| 点击此处可从《应用气象学报》浏览原始摘要信息 |
|
点击此处可从《应用气象学报》下载全文 |
