浏览全部资源
扫码关注微信
Published： 07 April 2023 ，
扫 描 看 全 文
白卓，张颢馨，马纯永，赵朝方，陈戈.2023.星载成像高度计双侧独立交叉定标方法.遥感学报，27（4）： 919-931
Bai Z，Zhang H X， Ma C Y， Zhao C F and Chen G. 2023. Bilateral independent cross-calibration method of the satellite-borne imaging altimeter. National Remote Sensing Bulletin， 27（4）：919-931
为通过数据处理提高SWOT的观测精度，本文采用双侧刈幅独立交叉定标对相位误差和倾角误差复合输入的情况进行误差估计。本文选取横跨经度100°和纬度60°的南太平洋东部地区，以HYCOM数据作为海洋真值，根据AVISO官网提供的SWOT和Jason-2（2016年10月前）轨道参数利用SWOT
simulator进行仿真采样，进行刈幅自交叉和星下点刈幅交叉实验。实验将90%的误差校正到4 cm内，近75%的交叉点残差的标准差降到2 cm内，较解算前提升一倍，表明在仪器精度较低时，双侧刈幅独立交叉定标的方法能够科学有效估计两种误差的复合输入值，显著降低了误差水平。
The Surface Water and Ocean Topography (SWOT) mission
which is scheduled to launch in 2022
will carry a Ka-band Radar Interferometer to characterize the ocean mesoscale and submesoscale circulation. The observation errors must be reduced to realize the observation target of the SWOT mission. Among the errors
the baseline inclination error caused by the inaccuracy of the baseline inclination measurement and the phase error induced by the phase mismatch in the process of interferometric imaging are difficult to eliminate. These two errors make the sea surface height measurement in the swath inaccurate and identification of the characteristics of mesoscale phenomena challenging. Therefore
the purpose of this article is to correct phase error and baseline roll error to achieve the observation goal.
Both errors are linear with across track distance from nadir. Assuming that all errors
except the phase and roll errors
have met the error budget requirements
a bilateral independent cross-calibration method is proposed to detect and mitigate the two spatial coherence errors. First
the errors of the left and right swaths in the experiment are calculated. Second
the observed values in the cross region are subtracted to reduce the influence of the ocean signal. Finally
the errors are estimated based on their linear correlation with the across track distance. The orbit parameters of SWOT and Jason-2 (before October 2016) provided by Archiving
Verification
and Interpretation of Satellite Oceanographic data are used for along-track sampling. The errors in the 25-day SWOT sample data are estimated by using the self-crossover and crossover (with Jason-2) methods.In the SWOT self-crossover
more than 90% of the error was corrected from 8 cm to 4 cm
and approximately 73% of the intersection-region standard deviation was adjusted from 6 cm to 2 cm.
In the SWOT crossover with Jason-2
approximately 86% of the error was corrected from 8 cm to 4 cm
and approximately 55% of the intersection-region standard deviation was adjusted from 6 cm to 2 cm. Based on the absolute value and standard deviation
the error inversion effect of the self-crossover and crossover (with Jason-2) methods on the intersection point is good. Results show that the bilateral independent cross-calibration method effectively estimates the overall error and significantly reduces the error level in the case of low instrument accuracy.The crossover method weakens the influence of a larger portion of the ocean signal
increases the weight of the error in the calculation process
and calculates the error through the matrix. Given that the characteristics that the phase error is different from the baseline inclination error
the left and right swaths are cross-calibrated separately to calculate the gradient slope value in the cross-track direction of the unilateral swath.
The calculated gradient slope value can be directly back-calculated to obtain the overall error and eliminate the error. The bilateral independent cross-calibration method not only inherits the ability of the cross-calibration algorithm to correct the baseline inclination error but also scientifically and effectively corrects the phase error. The experiment also suggests that the cross-calibration formula can be optimized based on the error characteristics to estimate other errors with gradient changes in the across track and contributes to error reduction.
交叉定标误差反演相位误差基线倾角误差干涉成像高度计
cross-calibrationerror-correctionphase errorbaseline roll errorinterferometric imaging altimeter
Ablain M, Philipps S, Picot N and Bronner E. 2010. Jason-2 global statistical assessment and cross-calibration with jason-1. Marine Geodesy, 33(S1): 162-185 [DOI: 10.1080/01490419.2010.487805http://dx.doi.org/10.1080/01490419.2010.487805]
Amores A, Jordà G, Arsouze T and Le Sommer J. 2018. Up to what extent can we characterize ocean eddies using present-day gridded altimetric products?. Journal of Geophysical Research: Oceans, 123(10): 7220-7236 [DOI: 10.1029/2018JC014140http://dx.doi.org/10.1029/2018JC014140]
Chavanne C P and Klein P. 2010. Can oceanic submesoscale processes be observed with satellite altimetry. Geophysical Research Letters, 37(22): L22602 [DOI: 10.1029/2010GL045057http://dx.doi.org/10.1029/2010GL045057]
Chelton D B and Schlax M G. 2003. The accuracies of smoothed sea surface height fields constructed from tandem satellite altimeter datasets. Journal of Atmospheric and Oceanic Technology, 20(9): 1276-1302 [DOI: 10.1175/1520-0426(2003)020<1276:TAOSSS>2.0.CO;2http://dx.doi.org/10.1175/1520-0426(2003)020<1276:TAOSSS>2.0.CO;2]
Dibarboure G, Labroue S, Ablain M, Fjortoft R, Mallet A, Lambin J and Souyris J C. 2012. Empirical cross-calibration of coherent SWOT errors using external references and the altimetry constellation. IEEE Transactions on Geoscience and Remote Sensing, 50(6): 2325-2344 [DOI: 10.1109/TGRS.2011.2171976http://dx.doi.org/10.1109/TGRS.2011.2171976]
Dibarboure G and Ubelmann C. 2014. Investigating the performance of four empirical cross-calibration methods for the proposed SWOT mission. Remote Sensing, 6(6): 4831-4869 [DOI: 10.3390/rs6064831http://dx.doi.org/10.3390/rs6064831]
Durand M, Fu L L, Lettenmaier D P, Alsdorf D E, Rodriguez E and Esteban-Fernandez D. 2010. The surface water and ocean topography mission: observing terrestrial surface water and oceanic submesoscale eddies. Proceedings of the IEEE, 98(5): 766-779 [DOI: 10.1109/JPROC.2010.2043031http://dx.doi.org/10.1109/JPROC.2010.2043031]
Enjolras V, Vincent P, Souyris J C, Rodriguez E, Phalippou L and Cazenave A. 2006. Performances study of interferometric radar altimeters: from the instrument to the global mission definition. Sensors, 6(3): 164-192 [DOI: 10.3390/s6030164http://dx.doi.org/10.3390/s6030164]
Faugere Y, Dorandeu J, Lefevre F, Picot N and Femenias P. 2006. Envisat ocean altimetry performance assessment and cross-calibration. Sensors, 6(3): 100-130 [DOI: 10.3390/s6030100http://dx.doi.org/10.3390/s6030100]
Fu L L and Ubelmann C. 2014. On the transition from profile altimeter to swath altimeter for observing global ocean surface topography. Journal of Atmospheric and Oceanic Technology, 31(2): 560-568 [DOI: 10.1175/JTECH-D-13-00109.1http://dx.doi.org/10.1175/JTECH-D-13-00109.1]
Gómez-Navarro L, Fablet R, Mason E, Pascual A, Mourre B, Cosme E and Le Sommer J. 2018. SWOT spatial scales in the western Mediterranean Sea derived from pseudo-observations and an Ad Hoc filtering. Remote Sensing, 10(4): 599 [DOI: 10.3390/rs10040599http://dx.doi.org/10.3390/rs10040599]
Gaultier L, Ubelmann C and Fu L L. 2016a. The challenge of using future SWOT data for oceanic field reconstruction. Journal of Atmospheric and Oceanic Technology, 33(1): 119-126 [DOI: 10.1175/JTECH-D-15-0160.1http://dx.doi.org/10.1175/JTECH-D-15-0160.1]
Gaultier L, Ubelmann C and Fu L L. 2016b. SWOT Simulator Documentation Release 2.3.0[EB/OL]. (2017-03-15)[2017-05-13]. https://SWOT.jpl.nasa.gov/documents/https://SWOT.jpl.nasa.gov/documents/
Lévy M, Iovino D, Resplandy L, Klein P, Madec G, Treguier A M, Masson S and Takahashi K. 2012. Large-scale impacts of submesoscale dynamics on phytoplankton: local and remote effects. Ocean Modelling, 43-44: 77-93 [DOI: 10.1016/j.ocemod.2011.12.003http://dx.doi.org/10.1016/j.ocemod.2011.12.003]
Ma C Y, Guo X X, Zhang H X, Di J K and Chen G. 2020. An investigation of the influences of SWOT sampling and errors on ocean eddy observation. Remote Sensing, 12(17): 2682 [DOI: 10.3390/rs12172682http://dx.doi.org/10.3390/rs12172682]
Metref S, Cosme E, Le Sommer J, Poel N, Brankart J M, Verron J and Navarro L G. 2019. Reduction of spatially structured errors in wide-swath altimetric satellite data using data assimilation. Remote Sensing, 11(11): 1336 [DOI: 10.3390/rs11111336http://dx.doi.org/10.3390/rs11111336]
Morrow R, Fu L L, Ardhuin F, Benkiran M, Chapron B, Cosme E, D’Ovidio F, Farrar J T, Gille S T, Lapeyre G, Le Traon P Y, Pascual A, Ponte A, Qiu B, Rascle N, Ubelmann C, Wang J B and Zaron E D. 2019. Global observations of fine-scale ocean surface topography with the Surface Water and Ocean Topography (SWOT) mission. Frontiers in Marine Science, 6: 232 [DOI: 10.3389/fmars.2019.00232http://dx.doi.org/10.3389/fmars.2019.00232]
Peral E and Esteban-Fernandez D. 2018. SWOT mission performance and error budget//IEEE International Geoscience and Remote Sensing Symposium. Valencia: IEEE: 8625-8628 [DOI: 10.1109/IGARSS.2018.8517385http://dx.doi.org/10.1109/IGARSS.2018.8517385]
Pujol M I, Dibarboure G, Le Traon P Y and Klein P. 2012. Using high-resolution altimetry to observe mesoscale signals. Journal of Atmospheric and Oceanic Technology, 29(9): 1409-1416 [DOI: 10.1175/JTECH-D-12-00032.1http://dx.doi.org/10.1175/JTECH-D-12-00032.1]
Rosen P A, Hensley S, Joughin I R, Li F K, Madsen S N, Rodriguez E and Goldstein R M. 2000. Synthetic aperture radar interferometry. Proceedings of the IEEE, 88(3): 333-382 [DOI: 10.1109/5.838084http://dx.doi.org/10.1109/5.838084]
Ubelmann C, Dibarboure G and Dubois P. 2018. A cross-spectral approach to measure the error budget of the SWOT altimetry mission over the ocean. Journal of Atmospheric and Oceanic Technology, 35(4): 845-857 [DOI: 10.1175/JTECH-D-17-0061.1http://dx.doi.org/10.1175/JTECH-D-17-0061.1]
Wang J B, Fu L L, Torres H S, Chen S M, Qiu B and Menemenlis D. 2019. On the spatial scales to be resolved by the surface water and ocean topography ka-band radar interferometer. Journal of Atmospheric and Oceanic Technology, 36(1): 87-99 [DOI: 10.1175/JTECH-D-18-0119.1http://dx.doi.org/10.1175/JTECH-D-18-0119.1]
相关文章
相关作者
相关机构
京公网安备11010802024621