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Eliminating the influence of Faraday rotation on passive microwave remote sensing from space

Yan Wei Lu Wen Shi Jian-Kang Ren Jian-Qi Wang Rui

Eliminating the influence of Faraday rotation on passive microwave remote sensing from space

Yan Wei, Lu Wen, Shi Jian-Kang, Ren Jian-Qi, Wang Rui
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  • Faraday rotation (FR) is one of the important error sources for passive microwave remote sensing from space. In this paper, the principle of FR variation is studied. The influence of FR on accuracy for microwave radiometer measurement is analyzed. We concentrate on FR correction both at 1.4 GHz for the orthogonal channel brightness temperature Tv and at 10.7 GHz for the correlative channel brightness temperature U. By using the simulated observational data of spaceborne microwave radiometry at one point in Hainan province in 2006, we compare the effects of two approaches: correction by auxiliary data (IRI model correction) and correction by polarimetric mode (Yueh and Ribó methods). Noise generated by the Monte Carlo mode is included in the simulation. Then a new method of using TEC data released by international GNSS service (IGS) is proposed. For correction of Tv at 1.4 GHz, correction made by polarimetric mode is better than that by auxiliary data. Yueh method is best in effectiveness while IRI model method is worst. For the correction of U at 10.7 GHz, the correction by polarimetric mode is invalid, only correction by auxiliary data is valid. IGS data method greatly improves the correction accuracy and can replace the method of IRI model for nearly real time correction or final data correction.
    • Funds:
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    Ulaby F T, Moore R K, Fung A K 1981 Microwave remote sensing: active and passive, vol. 1 (Massachusetts: Addison-Wesley Publishing Company)pp229―285

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    Martine S 2004 An introduction to ocean remote sensing (Cambridge: Cambridge University Press) pp201―227

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    Li Z, Wei E B, Tian J W 2007 Acta Phys. Sin. 56 3028 (in Chinese) [李志、魏恩泊、田纪伟 2007 物理学报 56 3028]

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    Barré H M J P, Duesmann B, Kerr Y H 2008 IEEE Trans Geosci Remote Sensing 46 587

    [5]

    Vine D M L, Lagerloef G S E, Torrusio S E 2010 Proceedings of the IEEE 98 688

    [6]

    Gaiser P W, Twarog E M, Li L 2004 IGARSS 2004 (New York: IEEE) pp371―374

    [7]

    Shi J K 2009 MS Thesis (Nanjing: Institute of Meteorology, PLA University of Science & Technology) (in Chinese) [施健康 2009硕士学位论文 (南京:解放军理工大学气象学院)]

    [8]

    Vine D M L, Abraham S 2002 IEEE Trans Geosci Remote Sensing 40 771

    [9]

    Abraham S, Vine D M L 2004 Adv Space Res. 34 2059

    [10]

    Abraham S, Vine D M L 2001 Adv Space Res. 27 153

    [11]

    Yueh S H 2000 IEEE Trans Geosci Remote Sensing 38 2434

    [12]

    Ribó S, Martín-Neira M 2004 IEEE Trans Geosci Remote Sensing 42 1405

    [13]

    Stokes G G 1852 Trans Cambridge Phil Soc. 9 399

    [14]

    Liu Y, Wei E B, Hong J L, Ge Y 2006 Chin. Phys. 15 2175

    [15]

    Vine D M L, Abraham S 2000 Microwave radiometry and remote sensing of the Earth's surface and atmosphere (Zeist: VSP) pp89―96

    [16]

    Shi J K, Yan W, Gong H Y 2009 J Microwave 25 79 (in Chinese) [施健康、严 卫、 龚洪运 2009 微波学报25 79]

    [17]

    Font J, Camps A, Borges A 2010 Proceedings of the IEEE 98 649

    [18]

    Vine D M L, Lagerloef G S E, Colomb F R 2007 IEEE Trans Geosci Remote Sensing 45 2040

    [19]

    Gaiser P W, Germain K M S, Twarog E M 2004 IEEE Trans Geosci Remote Sensing 42 2347

    [20]

    Meissner T, Wentz F J 2006 IEEE Trans Geosci Remote Sensing 44 506

    [21]

    Plonski M, Smith C 2001 Algorithm theoretical basis document (ATBD) for the conical-scanning microwave imager/sounder (CMIS) environmental data records (EDRs), volume 17 (Lexington: AER) pp1—132

    [22]

    Skou N 2003 Radio Science 38 24

    [23]

    Zine S, Boutin J, Font J 2008 IEEE Trans Geosci Remote Sensing 46 621

    [24]

    Pinori S, Crapolicchio R, Mecklenburg S 2008 MICRORAD 2008 (New York: IEEE) pp97―100

    [25]

    Yueh S H 1997 IEEE Trans Geosci Remote Sensing 35 1400

    [26]

    Rosenkranz P W 1998 Radio Science 33 919

    [27]

    Wang Z Z 2005 Ph. D. Dissertation (Beijing: Center for Space Science and Applied Research, Chinese Academy of Sciences) (in Chinese) [王振占 2005博士学位论文 (北京:中国科学院空间科学与应用研究中心)]

    [28]

    Xu X S, Hong Z J, Guo P, Liu R J 2010 Acta Phys. Sin. 59 2163 (in Chinese) [徐贤胜、洪振杰、郭 鹏、刘荣建 2010 物理学报 59 2163]

    [29]

    Yan W, Shi J K, Lu W 2010 J Infrared Millim Waves 29 225 (in Chinese) [严 卫、 施健康、陆 文 2010 红外与毫米波学报29 225]

  • [1]

    Ulaby F T, Moore R K, Fung A K 1981 Microwave remote sensing: active and passive, vol. 1 (Massachusetts: Addison-Wesley Publishing Company)pp229―285

    [2]

    Martine S 2004 An introduction to ocean remote sensing (Cambridge: Cambridge University Press) pp201―227

    [3]

    Li Z, Wei E B, Tian J W 2007 Acta Phys. Sin. 56 3028 (in Chinese) [李志、魏恩泊、田纪伟 2007 物理学报 56 3028]

    [4]

    Barré H M J P, Duesmann B, Kerr Y H 2008 IEEE Trans Geosci Remote Sensing 46 587

    [5]

    Vine D M L, Lagerloef G S E, Torrusio S E 2010 Proceedings of the IEEE 98 688

    [6]

    Gaiser P W, Twarog E M, Li L 2004 IGARSS 2004 (New York: IEEE) pp371―374

    [7]

    Shi J K 2009 MS Thesis (Nanjing: Institute of Meteorology, PLA University of Science & Technology) (in Chinese) [施健康 2009硕士学位论文 (南京:解放军理工大学气象学院)]

    [8]

    Vine D M L, Abraham S 2002 IEEE Trans Geosci Remote Sensing 40 771

    [9]

    Abraham S, Vine D M L 2004 Adv Space Res. 34 2059

    [10]

    Abraham S, Vine D M L 2001 Adv Space Res. 27 153

    [11]

    Yueh S H 2000 IEEE Trans Geosci Remote Sensing 38 2434

    [12]

    Ribó S, Martín-Neira M 2004 IEEE Trans Geosci Remote Sensing 42 1405

    [13]

    Stokes G G 1852 Trans Cambridge Phil Soc. 9 399

    [14]

    Liu Y, Wei E B, Hong J L, Ge Y 2006 Chin. Phys. 15 2175

    [15]

    Vine D M L, Abraham S 2000 Microwave radiometry and remote sensing of the Earth's surface and atmosphere (Zeist: VSP) pp89―96

    [16]

    Shi J K, Yan W, Gong H Y 2009 J Microwave 25 79 (in Chinese) [施健康、严 卫、 龚洪运 2009 微波学报25 79]

    [17]

    Font J, Camps A, Borges A 2010 Proceedings of the IEEE 98 649

    [18]

    Vine D M L, Lagerloef G S E, Colomb F R 2007 IEEE Trans Geosci Remote Sensing 45 2040

    [19]

    Gaiser P W, Germain K M S, Twarog E M 2004 IEEE Trans Geosci Remote Sensing 42 2347

    [20]

    Meissner T, Wentz F J 2006 IEEE Trans Geosci Remote Sensing 44 506

    [21]

    Plonski M, Smith C 2001 Algorithm theoretical basis document (ATBD) for the conical-scanning microwave imager/sounder (CMIS) environmental data records (EDRs), volume 17 (Lexington: AER) pp1—132

    [22]

    Skou N 2003 Radio Science 38 24

    [23]

    Zine S, Boutin J, Font J 2008 IEEE Trans Geosci Remote Sensing 46 621

    [24]

    Pinori S, Crapolicchio R, Mecklenburg S 2008 MICRORAD 2008 (New York: IEEE) pp97―100

    [25]

    Yueh S H 1997 IEEE Trans Geosci Remote Sensing 35 1400

    [26]

    Rosenkranz P W 1998 Radio Science 33 919

    [27]

    Wang Z Z 2005 Ph. D. Dissertation (Beijing: Center for Space Science and Applied Research, Chinese Academy of Sciences) (in Chinese) [王振占 2005博士学位论文 (北京:中国科学院空间科学与应用研究中心)]

    [28]

    Xu X S, Hong Z J, Guo P, Liu R J 2010 Acta Phys. Sin. 59 2163 (in Chinese) [徐贤胜、洪振杰、郭 鹏、刘荣建 2010 物理学报 59 2163]

    [29]

    Yan W, Shi J K, Lu W 2010 J Infrared Millim Waves 29 225 (in Chinese) [严 卫、 施健康、陆 文 2010 红外与毫米波学报29 225]

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  • Received Date:  10 November 2010
  • Accepted Date:  20 December 2010
  • Published Online:  15 September 2011

Eliminating the influence of Faraday rotation on passive microwave remote sensing from space

  • 1. Institute of Meteorology, PLA University of Science & Technology, Nanjing 211101, China

Abstract: Faraday rotation (FR) is one of the important error sources for passive microwave remote sensing from space. In this paper, the principle of FR variation is studied. The influence of FR on accuracy for microwave radiometer measurement is analyzed. We concentrate on FR correction both at 1.4 GHz for the orthogonal channel brightness temperature Tv and at 10.7 GHz for the correlative channel brightness temperature U. By using the simulated observational data of spaceborne microwave radiometry at one point in Hainan province in 2006, we compare the effects of two approaches: correction by auxiliary data (IRI model correction) and correction by polarimetric mode (Yueh and Ribó methods). Noise generated by the Monte Carlo mode is included in the simulation. Then a new method of using TEC data released by international GNSS service (IGS) is proposed. For correction of Tv at 1.4 GHz, correction made by polarimetric mode is better than that by auxiliary data. Yueh method is best in effectiveness while IRI model method is worst. For the correction of U at 10.7 GHz, the correction by polarimetric mode is invalid, only correction by auxiliary data is valid. IGS data method greatly improves the correction accuracy and can replace the method of IRI model for nearly real time correction or final data correction.

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