A parameter inversion for sea bridge based on high-resolution polarimetric synthetic aperture radar
-
摘要: 高分辨率SAR中,桥梁的各次反射回波表现为条带状,这给桥梁参数的反演带来了困难。本文提出了一种适用于高分辨率全极化SAR的水上桥梁参数反演方法。首先,通过极化散射特征区分出桥梁的单次、二次和三次反射回波目标。然后,结合微波反射和折射的原理,分析了高分辨SAR图像中桥梁的各次反射回波成条带状的原因,在此基础上提出了各次回波目标的提取方法和桥梁参数反演方法。最后,利用获取的AIRSAR数据反演了桥梁的上下桥高、桥厚、桥宽、桥长及桥塔高度等参数,通过与实测数据对比,结果表明,本文的方法能较准确地反演桥梁的各项参数,其中桥高误差仅为1.3%,结果也表明了在高分辨率条件下,C和L波段的桥梁参数反演能力相当。Abstract: 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.
-
Key words:
- high-resolution PolSAR /
- sea bridge /
- parameter inversion /
- multiband
-
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
点击查看大图
计量
- 文章访问数: 1076
- HTML全文浏览量: 48
- PDF下载量: 563
- 被引次数: 0