LIU Genwang, ZHANG Jie, ZHANG Xi, MENG Junmin, WANG Guoyu. A parameter inversion for sea bridge based on high-resolution polarimetric synthetic aperture radar[J]. Acta Oceanologica Sinica, 2016, 35(7): 68-75. doi: 10.1007/s13131-016-0912-z
Citation: LIU Genwang, ZHANG Jie, ZHANG Xi, MENG Junmin, WANG Guoyu. A parameter inversion for sea bridge based on high-resolution polarimetric synthetic aperture radar[J]. Acta Oceanologica Sinica, 2016, 35(7): 68-75. doi: 10.1007/s13131-016-0912-z

A parameter inversion for sea bridge based on high-resolution polarimetric synthetic aperture radar

doi: 10.1007/s13131-016-0912-z
  • Received Date: 2015-06-23
  • Rev Recd Date: 2015-10-12
  • Each reflection return of a bridge over water is displayed as wide stripe in a high-resolution synthetic aperture radar (SAR) image, which lead to difficulties in a parameter inversion. Therefore, a method of bridge parameter inversion is proposed for high-resolution full polarimetric SAR (PolSAR). First, the single, double and triplebounce returns from each component of the bridge are distinguished by the polarization scattering features. Then the reasons which lead to the backscatter echoes of the bridge over water being displayed as stripes are analyzed, using a principle of microwave reflection, as well as an extraction method for each reflection return, and a parameter retrieval method is obtained. Finally, the parameters of the bridge, including the height (top and bottom surfaces of the sea bridge), width, thickness, span, and height of the bridge tower, are retrieved using full polarimetric AIRSAR data. When a comparison of the measured data is completed, the results indicate that the proposed method can invert the parameters with a high accuracy, and that the inversion error of the bridge height (bottom surface) is only 1.3%. Moreover, the results also show that for the high-resolution SAR, the C and L-band images have the same ability in regards to parameter retrieval.
  • loading
  • Cadario E, Gross H, Hammer H, et al. 2008. Change detection for bridges over water in airborne and spaceborne sar data. In:Proceedings of the International Geoscience and Remote Sens-ing Symposium, IGARSS. Boston, MA, USA:IEEE, 479-482
    Cameron W L, Leung L K. 1990. Feature motivated polarization scat-tering matrix decomposition. In:Proceedings of Record of the IEEE 1990 International Radar Conference. Arlington, VA, USA:IEEE, 549-557
    Chaudhuri D, Samal A. 2008. An automatic bridge detection tech-nique for multispectral images. IEEE Transactions on Geoscience and Remote Sensing, 46(9):2720-2727
    Cloude S R, Pottier E. 1996. A review of target decomposition theor-ems in radar polarimetry. IEEE Transactions on Geoscience and Remote Sensing, 34(2):498-518
    Lee J S, Krogager E, Ainsworth T L, et al. 2006. Polarimetric analysis of radar signature of a manmade structure. IEEE Geoscience and Remote Sensing Letters, 3(4):555-559
    Lee J S, Pottier E. 2009. Polarimetric Radar Imaging:From Basics to Applications. Boca Raton:CRC Press
    Lüneburg E. 1995. Principles of radar polarimetry. Proceedings of the IEICE Transactions on the Electronics Theory, 78(10):1339-1345
    Robalo J, Lichtenegger J. 1999. ERS-SAR images a bridge. Earth Ob-servation Quarterly, ESA Technical Report, 7-10
    Schulz K, Cadario E, Gross H, et al. 2007. Detection and feature ex-traction of bridges in airborne and spaceborne SAR image data. In:Proceedings of SPIE 6749, Remote Sensing for Environment-al Monitoring, GIS Applications, and Geology VⅡ, 67490U. Florence, Italy:SPIE
    Soergel U, Thiele A, Cadario E, et al. 2007. Fusion of high-resolution inSAR data and optical imagery in scenes with bridges over wa-ter for 3D visualization and interpretation. In:Proceedings of Urban Remote Sensing Joint Event 2007. Paris:JURSE
    Sousa J J, Bastos L. 2013. Multi-temporal SAR interferometry reveals acceleration of bridge sinking before collapse. Natural Hazards and Earth System Sciences, 13(3):659-667
    Wang Wenguang, Sun Jinping, Hu Rui, et al. 2009. Knowledge-based bridge detection from SAR images. Journal of Systems Engin-eering and Electronics, 20(5):929-936
    Wang Haipeng, Xu Feng, Jin Yaqiu. 2009. Estimation of the bridge height over water using SAR image data. Journal of Remote Sensing, 13(3):385-390
    Wang Ying, Zheng Qinfen. 1998. Recognition of roads and bridges in SAR images. Pattern Recognition, 31(7):953-962
    Wegner J D, Soergel U. 2008. Bridge height estimation from com-bined high-resolution optical and SAR imagery. The Interna-tional Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B7):1071-1076
    Wu Wenyu, Yin Dong, Zhang Rong, et al. 2009. Bridge recognition of median-resolution SAR images using pun histogram entropy. Chinese Optics Letters, 7(7):572-575
    Zhang Shaoming, He Xiangchen, Zhang Xiaohu, et al. 2011. Auto-in-terpretation for Bridges over Water in High-resolution Space-borne SAR Imagery. Journal of Electronics & Information Tech-nology (in Chinese), 33(7):1706-1712
    Zhao Weizhou, Song Jianshe, Zhang Jie. 2006. Study on the detection algorithm of bridge over water in sAR image based on fuzzy theory. In:Proceedings of the 1st International Conference on Innovative Computing, Information and Control, 2006. Beijing:IEEE, 641-644
    Zhu Shanjiang, Levinson D, Liu H X, et al. 2008. The traffic and beha-vioral effects of the I-35W Mississippi River bridge collapse. Transportation Research:Part A. Policy and Practice, 44(10):771-784
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (1053) PDF downloads(563) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return