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GNSS-R信噪比信号在海面测高技术的研究综述

胡媛 钟李程 陈行杨 顾旺旺 刘卫

胡媛, 钟李程, 陈行杨, 顾旺旺, 刘卫. GNSS-R信噪比信号在海面测高技术的研究综述[J]. 全球定位系统, 2021, 46(4): 1-7. doi: 10.12265/j.gnss.2021011502
引用本文: 胡媛, 钟李程, 陈行杨, 顾旺旺, 刘卫. GNSS-R信噪比信号在海面测高技术的研究综述[J]. 全球定位系统, 2021, 46(4): 1-7. doi: 10.12265/j.gnss.2021011502
HU Yuan, ZHONG Licheng, CHEN Xingyang, GU Wangwang, LIU Wei. A summary of research on GNSS-R signal-to-noise ratio signal height measurement technology on the sea[J]. GNSS World of China, 2021, 46(4): 1-7. doi: 10.12265/j.gnss.2021011502
Citation: HU Yuan, ZHONG Licheng, CHEN Xingyang, GU Wangwang, LIU Wei. A summary of research on GNSS-R signal-to-noise ratio signal height measurement technology on the sea[J]. GNSS World of China, 2021, 46(4): 1-7. doi: 10.12265/j.gnss.2021011502

GNSS-R信噪比信号在海面测高技术的研究综述

doi: 10.12265/j.gnss.2021011502
基金项目: 国家自然科学基金(52071199);上海市自然科学基金(19ZR1422800,18ZR1417100);上海市浦江人才计划(18ZR1417100)
详细信息
    作者简介:

    胡媛:(1981—),女,博士,副教授,主要研究方向为海洋遥感、GNSS-R等研究

    刘卫:(1981—),男,副教授,研究方向为GNSS遥感、组合导航技术

    通信作者:

    刘卫 E-mail:liu@satnav.cn

  • 中图分类号: P228.4;P731.23

A summary of research on GNSS-R signal-to-noise ratio signal height measurement technology on the sea

  • 摘要: 自全球卫星导航反射信号(GNSS-R)概念提出以来,GNSS-R被广泛应用于遥感方面. 如海面测高,海面风场反演,海冰检测等多个方面. 文中主要介绍了GNSS-R遥感技术在海面测高的应用和研究进展,着重介绍了基于信噪比(SNR)数据测量方法的研究进展,简述了SNR数据测量方法所涉及的理论和信号处理的办法,并根据现有的研究进展,对未来海面测高的发展方向进行展望.

     

  • 图  1  GNSS-R海面测高几何关系图

    图  2  SNR信号和拟合的趋势项

    图  3  LSP分析结果

    图  4  小波去噪原理图

    表  1  LSP法和拟合法反演结果 m

    方法平均误差均方根误差(RMSE)
    LSP0.0110.02875
    拟合法0.0080.02485
    下载: 导出CSV

    表  2  LSP法、加窗LSP法和小波法反演结果

    方法标准差/cm相关系数反演点数
    LSP13.090.96432
    WinLSP22.850.961 770
    Wavelet14.470.9629 703
    下载: 导出CSV
  • [1] 陈俊任, 周晓华, 余彬彬. 海洋测绘中压力式验潮仪零点漂移修正方法[J]. 测绘技术装备, 2018, 20(4): 84-86, 77. DOI: 10.3969/j.issn.1674-4950.2018.04.026
    [2] HALL C D, CORDEY R. Multistatic scatterometry[C]//International Geoscience and Remote Sensing Symposium, 'Remote Sensing: Moving Toward the 21st Century, 1988. DOI: 10.1109/IGARSS.1988.570200
    [3] CAMPS A, PARK H, PABLOS M, et al. Sensitivity of GNSS-R spaceborne observations to soil moisture and vegetation[J]. IEEE journal of selected topics in applied earth observations and remote sensing, 2016, 9(10): 1-13. DOI: 10.1109/JSTARS.2016.2588467
    [4] CLARIZIA M P, PIERDICCA N, COSTANTINI F, et al. Analysis of CYGNSS data for soil moisture retrieval[J]. IEEE journal of selected topics in applied earth observations and remote sensing, 2019, 12(7): 2227-2235. DOI: 10.1109/JSTARS.2019.2895510
    [5] EROGLU O, KURUM M, BOYD D R, et al. High spatio-temporal resolution CYGNSS soil moisture estimates using artificial neural networks[J]. Remote sensing, 2019, 11(19): 2272. DOI: 10.3390/rs11192272
    [6] KATZBERG S J, TORRES O, GRANT M S, et al. Utilizing calibrated GPS reflected signals to estimate soil reflectivity and dielectric constant: results from SMEX02[J]. Remote sensing of environment, 2006, 100(1): 17-28. DOI: 10.1016/j.rse.2005.09.015
    [7] ARROYO A A, CAMPS A, AGUASCA A, et al. Dual-polarization GNSS-R interference pattern technique for soil moisture mapping[J]. IEEE journal of selected topics in applied earth observations and remote sensing, 2014, 7(5): 1533-1544. DOI: 10.1109/JSTARS.2014.2320792
    [8] CALABIA A, MOLINA I, JIN S G. Soil moisture content from GNSS reflectometry using dielectric permittivity from fresnel reflection coefficients[J]. Remote sensing, 2020, 12(1): 122. DOI: 10.3390/rs12010122
    [9] JIN S G, NAJIBI N. Sensing snow height and surface temperature variations in greenland from GPS reflected signals[J]. Advances in space research, 2014, 53(11): 1623-1633. DOI: 10.1016/j.asr.2014.03.005
    [10] JIN S G, QIAN X D, KUTOGLU H. Snow depth variations estimated from GPS-reflectometry: a case study in Alaska from L2P SNR data[J]. Remote sensing, 2016, 8(1): 63. DOI: 10.3390/rs8010063
    [11] MCCREIGHT J L, SMALL E E, LARSON K M. Snow depth, density, and SWE estimates derived from GPS reflection data: validation in the western US[J]. Water resources research, 2014, 50(8): 6892-6909. DOI: 10.1002/2014WR015561
    [12] NAJIBI N, JIN S G. Physical reflectivity and polarization characteristics for snow and ice-covered surfaces interacting with GPS signals[J]. Remote sensing, 2013, 5(8): 4006-4030. DOI: 10.3390/rs5084006
    [13] NAJIBI N, JIN S G, WU X R. Validating the variability of snow accumulation and melting from GPS-reflected signals: forward modeling[J]. IEEE transactions on antennas and propagation, 2015, 63(6): 2646-2654. DOI: 10.1109/TAP.2015.2414950
    [14] MALIK J S, BHATTI U I. Remote sensing of ocean, ice and land surfaces using bistatically scattered GNSS signals from low earth orbit[C]//The 4th International Conference on Aerospace Science and Engineering (ICASE), 2015. DOI: 10.1109/ICASE.2015.7489519
    [15] YAN Q Y, HUANG W M. Spaceborne GNSS-R sea ice detection using delay-doppler maps: first results from the UK TechDemoSat-1 mission[J]. IEEE journal of selected topics in applied earth observations and remote sensing, 2016, 9(10): 4795-4801. DOI: 10.1109/JSTARS.2016.2582690
    [16] YAN Q Y, HUANG W M. Sea ice sensing from GNSS-R data using convolutional neural networks[J]. IEEE geoscience and remote sensing letters, 2018, 15(10): 1510-1514. DOI: 10.1109/LGRS.2018.2852143
    [17] YAN Q Y, HUANG W M. Detecting sea ice from TechDemoSat-1 data using support vector machines with feature selection[J]. IEEE journal of selected topics in applied earth observations and remote sensing, 2019, 12(5): 1409-1416. DOI: 10.1109/JSTARS.2019.2907008
    [18] LI C, HUANG W M. Sea surface oil slick detection from GNSS-R delay-doppler maps using the spatial integration approach[C]//IEEE Radar Conference (RADAR), 2013. DOI: 10.1109/RADAR.2013.6585990
    [19] VALENCIA E, CAMPS A, PARK H, et al. Oil slicks detection using GNSS-R[C]//IEEE International Geoscience and Remote Sensing Symposium, 2011. DOI: 10.1109/IGARSS.2011.6050203
    [20] VALENCIA E, CAMPS A, RODRIGUEZ-ALVAREZ N, et al. Using GNSS-R imaging of the ocean surface for oil slick detection[J]. IEEE journal of selected topics in applied earth observations and remote sensing, 2012, 6(1): 217-223. DOI: 10.1109/JSTARS.2012.2210392
    [21] 陈闪闪, 张云, 洪中华, 等. GNSS 反射信号海面溢油回波 DDM 仿真研究[J]. 全球定位系统, 2017, 42(3): 15-19.
    [22] MARTIN-NEIRA M. A passive reflectometry and interferometry system (PARIS): application to ocean altimetry[J]. ESA journal, 1993, 17(4): 331-355.
    [23] SOULAT F, CAPARRINI O, GERMAIN P, et al. Sea state monitoring using coastal GNSS-R[J]. Geophysical research letters, 2004, 31(21): 303. DOI: 10.1029/2004GL020680
    [24] LARSON K M, LÖFGREN J S, HAAS R. Coastal sea level measurements using a single geodetic GPS receiver[J]. Advances in space research, 2013, 51(8): 1301-1310. DOI: 10.1016/j.asr.2012.04.017
    [25] RIBOT M A, KUCWAJ J C, BOTTERON C, et al. Normalized GNSS interference pattern technique for altimetry[J]. Sensors (basel), 2014, 14(6): 10234-10257. DOI: 10.3390/s140610234
    [26] CARDELLACH E, FABRA F, NOGUÉS-CORREIG O, et al. GNSS-R ground-based and airborne campaigns for ocean, land, ice, and snow techniques: application to the GOLD-RTR data sets[J]. Radio science, 2011, 46(6): RS0C04. DOI: 10.1029/2011RS004683
    [27] GEREMIA-NIEVINSKI F G, LARSON K M. Inverse modeling of GPS multipath for snow depth estimation—part Ⅱ: application and validation[J]. IEEE transactions on geoscience and remote sensing, 2014, 52(10): 6564-6573. DOI: 10.1109/TGRS.2013.2297688
    [28] 吴夏平, 王福明. 基于最小二乘法原理的趋势项处理研究[J]. 微计算机信息, 2008, 24(30): 254-255. DOI: 10.3969/j.issn.1008-0570.2008.30.102
    [29] STRANDBERG J, HOBIGER T, HAAS R. Improving GNSS-R sea level determination through inverse modeling of SNR data[J]. Radio science, 2016, 51(8): 1286-1296. DOI: 10.1002/2016RS006057
    [30] 李惟, 朱云龙, 王峰, 等. GNSS 多径信号模型及测高方法[J]. 北京航空航天大学学报, 2018, 44(6): 1239-1245.
    [31] LOMB N R. Least-squares frequency analysis of unequally spaced data[J]. Astrophysics and space science, 1976, 39(2): 447-462. DOI: 10.1007/BF00648343
    [32] SCARGLE J D. Studies in astronomical time series analysis. Ⅱ-Statistical aspects of spectral analysis of unevenly spaced data[J]. The astrophysical journal, 1982(263): 835-853. DOI: 10.1086/160554
    [33] 马秀红, 曹继平, 董晟飞. 小波分析及其应用[J]. 微机发展, 2003, 13(8): 58-61.
    [34] WANG X L, ZHANG Q, ZHANG S C. Water levels measured with SNR using wavelet decomposition and lomb–scargle periodogram[J]. GPS solutions, 2018, 22(1): 22. DOI: 10.1007/s10291-017-0684-8
    [35] CHEN F, LIU L L, GUO F. Sea surface height estimation with multi-GNSS and wavelet de-noising[J]. Scientific reports, 2019, 9(1): 15181. DOI: 10.1038/s41598-019-51802-9
    [36] 苏晓容, 张云, 韩彦岭, 等. 岸基 GNSS 单天线潮位高度小波分析反演[J]. 导航定位学报, 2019, 7(4): 87-93. DOI: 10.3969/j.issn.2095-4999.2019.04.016
    [37] 王杰, 何秀凤, 王笑蕾, 等. 小波分析在 GNSS-IR 潮位反演中的应用[J]. 导航定位学报, 2020, 8(2): 82-89. DOI: 10.3969/j.issn.2095-4999.2020.02.014
    [38] MALLAT S G. A theory for multiresolution signal decomposition: the wavelet representation[J]. IEEE transactions on pattern analysis and machine intelligence, 1989, 11(7): 674-693. DOI: 10.1109/34.192463
    [39] KALMAN R E. A new approach to linear filtering and prediction problems[J]. Journal of basic engineering, 1960(82D): 35-45. DOI: 10.1115/1.3662552
    [40] JAZWINSKI A H. Stochastic process and filtering theory, academic press[M]. A subsidiary of Harcourt Brace Jovanovich Publishers, 1970.
    [41] WAN E A, MERWE R V D. The unscented Kalman filter for nonlinear estimation[C]//IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No. 00EX373), 2000: 153-158. DOI: 10.1109/ASSPCC.2000.882463
    [42] STRANDBERG J, HOBIGER T, HAAS R. Real-time sea-level monitoring using Kalman filtering of GNSS-R data[J]. GPS solutions, 2019, 23(3): 61. DOI: 10.1007/s10291-019-0851-1
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出版历程
  • 收稿日期:  2021-01-15
  • 网络出版日期:  2021-08-11

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