Detection and analysis of television frequency interference from an FY-3C microwave radiation imager

Zehua ZHOU; Xiaolei ZOU; Zhengkun QIN

doi:10.11834/jrs.20176364

Views : 0 下载量: 52 CSCD: 5 更多指标

PDF
Export
Share
Collection
Album

Detection and analysis of television frequency interference from an FY-3C microwave radiation imager
Vol. 21, Issue 5, Pages: 689-701(2017)
Published： 2017-9 ，

Accepted： 12 April 2017
DOI： 10.11834/jrs.20176364

扫描看全文

周泽华, 邹晓蕾, 秦正坤. 2017. FY-3C微波成像仪电视信号干扰识别和分析. 遥感学报, 21(5): 689–701

Zhou Z H, Zou X L and Qin Z K. 2017. Detection and analysis of television frequency interference from an FY-3C microwave radiation imager. Journal of Remote Sensing, 21(5): 689–701
周泽华, 邹晓蕾, 秦正坤. 2017. FY-3C微波成像仪电视信号干扰识别和分析. 遥感学报, 21(5): 689–701 DOI： 10.11834/jrs.20176364.

Zhou Z H, Zou X L and Qin Z K. 2017. Detection and analysis of television frequency interference from an FY-3C microwave radiation imager. Journal of Remote Sensing, 21(5): 689–701 DOI： 10.11834/jrs.20176364.

摘要

由于卫星微波成像仪频率的非保护性，微波成像仪资料受到相近频率的无线电信号干扰影响，主要干扰源于洋面反射的静止电视卫星信号。为提高微波成像仪资料的准确性，尤其是洋面资料的可用性，对电视卫星信号干扰的检测和特征分析尤为重要。中国风云3号C星(FY-3C)上搭载了微波成像仪。本文使用标准化主成分分析法来识别FY-3C微波成像仪的电视卫星干扰信号，并分析电视卫星信号干扰的主要空间特征。研究表明，FY-3C微波成像仪中心频率为10.65 GHz和18.7 GHz的4个低频通道受到卫星信号干扰。10.65 GHz通道在欧洲海域英吉利海峡和地中海西部希腊沿岸地区受到电视卫星信号干扰，并且干扰信号位置和强度与FY-3C卫星和欧洲静止电视卫星相对空间位置有关；18.7 GHz通道主要受到美国电视卫星的干扰，在北美东、西沿岸海域都存在干扰信号。FY-3C微波成像仪在中国海域不受电信号干扰影响，主要因为中国静止电视卫星频率与微波成像仪各通道频率不一样。

Abstract

Observations of a satellite Microwave Radiation Imager (MWRI) are easily interfered by signals of active remote sensing because of their similar frequency. The primary source of interference over oceans is the reflected signal of geostationary television (TV) satellites by the ocean surface. The accurate detection of such interferences is largely important for the effective use of MWRI observations and an essential preprocessing step of the MWRI data onboard the FY-3C satellite. A Normalized Principal Component Analysis Method (NPCA) is used to detect the TV Frequency Interference (TFI) signals over oceans. High correlations exist among the different MWRI channels

but the RFI signal eliminates these correlations. Hence

NPCA can detect the TFI signal by employing this aspect. The TFI signals of the MWRI at 10.65 GHz horizontal polarization over oceans are distributed widely near the coastal areas of Europe

especially the English Channel and western parts of the Mediterranean Sea. The TFI signal definitively originates from the hot bird

and its intensity is related to the angle between the MWRI incidence and geostationary satellite TV signals reflection. The threshold of the TFI signals is defined to quantify the TFI intensity. The TFI signals at 18.7 GHz are observed over the offshore marine areas of North America. As expected

no RFI signal is detected near the coastal areas of China because the geostationary satellite TV frequency over China is different from those of MWRI channels. The NPCA method can detect TFI signals over oceans. The distribution of TFI signals are in Europe at 10.65 GHz and North America at 18.7 GHz. The intensity of the TFI signals is completely related to the Glint angle. TFI signals evidently affect the result of the retrieval production. Correcting and eliminating TFI signals will be pursued in future studies. Clear brightness temperature data will also be adopted in retrieval production and data assimilation.

关键词

风云3号C星(FY-3C)微波成像仪海洋电视信号干扰识别

Keywords

FY-3CMicrowave Radiation Imager (MWRI)oceantelevision frequency interferencedetection

references

Adams I S, Bettenhausen M H, Gaiser P W and Johnston W. 2010. Identification of ocean-reflected radio-frequency interference using WindSat retrieval chi-square probability. IEEEGeoscience and Remote Sensing Letters, 7(2): 406–410

Dong C H, Yang J, Yang Z D, Lu N M, Shi J M, Zhang P, Liu Y J, Cai B and Zhang W J. 2009. An overview of a new Chinese weather satellite FY-3A. Bulletin of the American Meteorological Society, 90(10): 1531–1544

冯呈呈, 赵虹. 2015. FY-3B微波成像仪海洋数据无线电干扰识别. 遥感学报, 19(3): 465–475

Feng C C and Zhao H. 2015. Identification of radio-frequency interference signal from FY-3B microwave radiation imager over ocean. Journal of Remote Sensing, 19(3): 465–475

Gaiser P W, St.Germain KM, Twarog EM, Poe GA, Purdy W, Richardson D, Grossman W, Jones WL, Spencer D, Golba G, Cleveland J, Choy L, Bevilacqua RM and Chang PS 2004. The WindSatspacebornePolarimetric microwave radiometer: sensor description and early orbit performance. IEEE Transactions on Geoscience and Remote Sensing, 42(11): 2347–2361

官莉, 夏仕昌, 张思勃. 2015. 大面积水体上空星载微波辐射计的干扰识别. 应用气象学报, 26(1): 22–31

Guan L, Xia S C and Zhang S B. 2015. Identifying the interference of spaceborne microwave radiometer over large water area. Journal of Applied Meteorological Science, 26(1): 22–31

Hollinger J P, Peirce J L and Poe G A. 1990. SSM/I instrument evaluation. IEEE Transactions on Geoscience and Remote Sensing, 28(5): 781–790

扈培信. 2011. FY-3B微波成像仪数据质量评价与参数反演. 青岛: 中国海洋大学

Hu P X. 2011. Evaluation and Retrival of FY-3B Micro Wave Radiation Imager Brightness Temperature. Qingdao: Ocean University of China

Kawanishi T, Sezai T, Ito Y, ImaokaK, Takeshima T, Ishido Y, Shibata A, Miura M, Inahata H and Spencer RW. 2003. The advanced microwave scanning radiometer for the earth observing system (AMSR-E), NASDA's contribution to the EOS for global energy and water cycle studies. IEEE Transactions on Geoscience and Remote Sensing, 41(2): 184–194

Kummerow C, Barnes W, KozuT, ShiueJ andSimpson J. 1998. The tropical rainfall measuring mission (TRMM) sensor package. Journal of Atmospheric and Oceanic Technology, 15(3): 809–817

Li L, Njoku E G, Im E, Chang P S and St. Germain K. 2004. A preliminary survey of radio-frequency interference over the U.S. in aqua AMSR-E data.IEEE Transactions on Geoscience and Remote Sensing, 42(2): 380–390 [DOI: 10.1109/TGRS. 2003.817195]

Li L, Gaiser P W, Bettenhausen M H and Johnston W. 2006. WindSat radio-frequency interference signature and its identification over land and ocean. IEEE Transactions onGeoscience and Remote Sensing, 44(3): 530–539

Njoku E G, Ashcroft P,Chan TK and Li L. 2005. Global survey and statistics of radio-frequency interference in AMSR-E land observations. IEEE Transactions on Geoscience and Remote Sensing, 43(5): 938–947

Oki T, Imaoka KandKachi M. 2010. AMSR instruments on GCOM-W1/2: concepts and applications//Proceedings of 2010 IEEE International Geoscience and Remote Sensing Symposium. Honolulu, HI:IEEE: 1363–1366 [DOI: 10.1109/IGARSS.2010.5650001]

王振占. 2003. 用19.35 GHz星载微波辐射计(SSM/I)亮温反演海面风速. 海洋技术学报, 22(2): 1–6

Wang Z Z. 2003. A Model for inversing sea surface wind speeds by using SSM/I 19.35 GHZ vertical and horizontal brightness temperatures. Ocean Technology, 22(2): 1–6

Zhao J, Zou X L and Weng F Z. 2013. WindSat radio-frequency interference signature and its identification over greenland and antarctic. IEEE Transactions on Geoscience and Remote Sensing, 51(9): 4830–4839

邹晓蕾. 2012. 极轨气象卫星微波成像仪资料. 气象科技进展, 2(3): 45–50

Zou X L. 2012. Serial of applications of satellite observations Introduction to microwave imager radiance observations from polar-orbiting meteorological satellites. Advances in Meteorological Science and Technology, 2(3): 45–50

Zou X L, Zhao J, Weng F Z and Qin Z K. 2012. Detection of radio-frequency interference signal over land from FY-3B Microwave Radiation Imager (MWRI). IEEE Transactions onGeoscience and Remote Sensing, 50(12): 4994–5003

Zou X L, Tian X X and Weng F Z. 2014. Detection of television frequency interference with satellite microwave imager observations over oceans. Journal of Atmospheric and Oceanic Technology, 31(12): 2759–2776

Alert me when the article has been cited

提交

Airborne LiDAR bathymetry sediment classification considering the optimal features by using seabed point cloud

Progress of the study on coral reef remote sensing