Study on the effect of radio frequency interference on the accuracy of SMOS sea surface salinity data
-
摘要: SMOS卫星数据发布以来,相关学者针对海表盐度数据开展了大量的真实性检验工作,但是在受无线射频干扰(RFI)影响海域开展的相关工作很少。本文以西太平洋海域为研究区域,选择合理的时空匹配窗口,将WOD13实测海表盐度数据与SMOS卫星单轨海表盐度数据进行数据匹配,采用统计学方法开展SMOS卫星数据真实性检验,并分析RFI对SMOS卫星数据的影响。结果表明,SMOS卫星受分布在西太平洋沿岸射频干扰源的影响,RFI污染高风险区单轨L2数据准确度相对较低,最优仅为3.45,RFI污染低风险区的卫星数据准确度最优为1.07,可见,RFI对单轨卫星数据准确度的影响很大,最终导致西太平洋海域西部大面积海域数据缺失,尤其是中国近海海域,如何检测和减缓RFI对卫星数据的影响是亟待解决的问题。Abstract: Scholars have done a lot of work in the assessment and validation of SMOS sea surface salinity (SSS) data since SMOS satellite data released, but rarely work have done in the Western Pacific Ocean(WPO) influenced by radio frequency interference (RFI), it will be of important significance on understanding of RFI influence on SMOS SSS date. The main method is matching the WOD13 in-situ SSS data with SMOS half-orbit SSS data, assessing the accuracy of SMOS data by statistics method. Results suggest that since SMOS is polluted by RFI sources located in west coast of the WPO, the RMSE of SMOS L2 SSS data in high risk area of RFI pollution is relatively low, and the highest RMSE can be achieved on 3.45, thus it can be seen that the RFI have a significant influence on SMOS satellite in the WPO, this has resulted in the loss of significant amount of data, especially in the China sea, how to detect and mitigate RFI is a scientific problem to be solved.
-
Key words:
- radio frequency interference /
- microwave radiometry /
- SMOS satellite /
- sea surface salinity /
- validation
-
陈建, 张韧, 安玉柱, 等. SMOS卫星遥感海表盐度资料处理应用研究进展[J]. 海洋科学进展, 2013, 31(2): 295-304. Chen Jian, Zhang Ren, An Yuzhu, et al. Overview on processing and applying on the SMOS satellite remotely sensed sea surface salinity products[J]. Advances in Marine Science, 2013, 31(2): 295-304. Yin Xiaobin, Boutin J, Spurgeon P. First assessment of SMOS data over open ocean: Part I—Pacific Ocean [J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(5): 1648-1661. Font J, Camps A, Borges A, et al. SMOS: The challenging sea surface salinity measurement from space[J]. Proceedings of the IEEE, 2010, 98(5): 649-665. Kerr Y H, Wigneron J P, Boution J, et al. The SMOS mission: New tool for monitoring key elements of the global water cycle[J]. Proceedings of the IEEE, 2010, 98(5): 666-687. Banks C, Gommenginger C, Srokosz M, et al. Validating SMOS ocean surface salinity in the Atlantic with Argo and operational ocean model data[J]. IEEE Geoscience and Remote Sensing Society, 2012, 50(5): 1688-1702. Boutin J, Reul N, Font J. Sea surface salinity from SMOS satellite: complementarity to in situ observations[C]//WCRP Open Science Conference Climate Research in Service to Society, Denver, 2011. Boutin J, Martin N, Yin Xiaobin. First assessment of SMOS data over open ocean: part Ⅱ-sea surface salinity[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(5): 1662-1675. Boutin J, Martin N, Reverdin G. Sea surface freshening inferred from SMOS and ARGO salinity:impact of rain[J]. Ocean Science, 2013, 9(1): 183-192. 王新新, 杨建洪, 赵冬至, 等. SMOS卫星盐度数据在中国近岸海域的准确度评估[J]. 海洋学报, 2013, 35(5): 169-176. Wang Xinxin, Yang Jianhong, Zhao Dongzhi, et al. SMOS satellite salinityaccuracy assessment in the China coastal areas[J].Haiyang Xuebao, 2013, 35(5): 169-176. Ren Yongzheng, Dong Qing, He Mingxia. Preliminary validation of SMOS sea surface salinity measurements in the South China Sea[J]. Chinese Journal of Oceanology and Limnology, 2015, 33(1): 262-271. Oliva R, Daganzo E, Kerr Y H, et al. SMOS radio frequency interference scenario: status and actions taken to improve the RFI environment in the 1400-1427-MHz passive band[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(5): 1427-1439. Johanson J, Mohammed P, Piemeier J, et al. Soil moisture active passive (SMAP) microwave radiometer radio-frequency interference(RFI) mitigation: Algorithm updates and performance assessment [C]//2016 IEEE International Geoscience and Remote Sensing Symposium(IGARSS), 2016. 王新新, 王祥, 韩震, 等. 基于L波段Stokes参数遥感数据射频干扰检测及特性分析[J]. 电子与信息学报, 2015, 37(10): 2342-2348. Wang Xinxin, Wang Xiang, Han Zhen, et al. Radio frequency interference detection and characteristic analysis based on the L band Stokes parameters remote sensing data[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2342-2348. Zine S, Boutin J, Font J, et al. Overview of the SMOS sea surface salinity processor[J]. IEEE Transaction on Geoscience and Remote Sensing, 2008, 46(3): 621-644.
点击查看大图
计量
- 文章访问数: 770
- HTML全文浏览量: 7
- PDF下载量: 692
- 被引次数: 0