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研究了分形粗糙面的成像问题. 分形粗糙面能够较好的逼近真实环境, 采用带限形式的Weierstrass-Mandelbrot函数建立了分形粗糙面几何模型, 对分形粗糙面参数的选取进行了讨论. 对大尺度粗糙面散射问题提出了一种基于大面元的Kirchhoff近似方法, 采用面元模型来计算粗糙面总的后向散射场以及每一个面元的后向散射场, 并对面元的尺寸选取进行了研究, 通过与解析解进行对比证明了该方法的正确性. 在分形理论建立的确定性粗糙面几何模型与面元的Kirchhoff方法获取的散射场的基础上, 采用正侧视条带式成像模式, 并选用距离多普勒算法对不同分形参数的粗糙面进行合成孔径雷达(SAR) 成像模拟, 结果显示从SAR像中可以清晰地观察到不同分形参数对粗糙面几何轮廓的影响. 该研究包括了从环境模型、电磁模型到SAR成像技术在内的完整的分形环境SAR像模拟过程, 仿真结果显示出分形环境的SAR像特点, 这对基于分形理论的自然环境的遥感探测以及参数反演具有一定的理论支撑作用.
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关键词:
- 分形粗糙面 /
- Weierstrass-Mandelbrot函数 /
- Kirchhoff /
- 合成孔径雷达成像
The synthetic aperture radar imaging of fractal rough surface is studied. The natural surface can be very accurately described in terms of fractal geometry. Such a two-dimensional fractional Brownian motion (FBM) stochastic process provides a very sound description of natural surface. The samples of band-limited FBM process are realized by using physical Weierstrass-Mandelbrot function. The parameters of fractal rough surface are discussed and how to choose the value is analyzed. The roughness is mostly determined by the Hurst coefficient or the fractal dimension. In the actual simulation, a fractal rough surface can be seen as the superposition of finite sinusoidal tones, and any scattering measurement is limited to a finite set of scales. In this paper, the surface is described with two-scale model, i. e., locally approximated by plane facets with dimension smaller than that of resolution cells, but much larger than wavelength. Because this paper focuses on the texture of the synthetic aperture radar (SAR) image and the overall image texture is related to the macroscopic scale, the microscopic roughness superimposed on the facets is neglected. For the macroscopic scale scattering problem, a facet Kirchhoff approach is proposed. The fractal rough surface consists of many triangle facets, and the scatter field of each facet can be obtained by the facet Kirchhoff approach. The principle of dimension selection is studied. The dimension of facet must follow the principle that the surface profile is not damaged. At the same time, the facet dimension should be as large as possible in order to increase the efficiency of imaging. After establishing the fractal geometry model and obtaining the field from each facet, the SAR image can be realized through Rang-Doppler method in the stripmap mode. The results show that in the SAR image, the effects of fractal parameters on the rough surface can be obviously observed. The peaks and ravines of rough surface are obviously observed at low fractal dimension or high Hurst coefficient. However, when the fractal dimension gets higher or Hurst coefficient gets higher, the peaks and ravines disappear because the surface becomes rougher and diffuse scattering is enhanced. The effect of fractal parameter on the SAR image can be specifically expressed with entropy and angle second moment. With the increase of fractal dimension D, the texture of SAR image behaves more randomly and disorderly. So the entropy of SAR image becomes larger and the angle second moment of SAR image becomes smaller. The texture of SAR image is also related to the squint angle and frequency of incidence wave. The relative roughness will become larger when the squint angle and frequency of incidence wave become larger. The research on a complete fractal surface SAR imaging system consists of establishing the environmental model, developing the electromagnetic scattering model, and using the SAR imaging technique. The achievements show the characteristics of fractal rough surface SAR image, which have a theoretical support for natural environment remote sensing and the environment parameters inversion.-
Keywords:
- fractal rough surface /
- Weierstrass-Mandelbrot function /
- Kirchhoff /
- synthetic aperture radar image
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[4] IoIodice A, Natale A, Riccio D 2013 IEEE Trans. Anten. Propag. 61 2156
[5] Ruello G, Sanchez P B, Iodice A, Mallorqui J, Riccio D, Broquetas A, Franceschetti G 2010 IEEE Trans. Geosci. Remot. 48 1777
[6] Franceschetti G, Iodice A 1999 Radio Sci. 34 1043
[7] Franceschetti G, Iodice A, Riccio D, Ruello G 2005 IEEE Trans. Geosci. Remot. 43 1115
[8] Schelrath J H, denhofer P E 2005 Electro. Lett. 41
[9] Guo L X, Wang Y H, Wu Z S 2005 Acta Phys. Sin. 54 96 (in Chinese) [郭立新, 王运华, 吴振森 2005 物理学报 54 96]
[10] Ren X C, Guo L X 2009 Acta Phys. Sin. 58 1627 (in Chinese) [任新成, 郭立新 2009 物理学报 58 1627]
[11] Ren X C, Guo L X 2008 Chin. Phys. B 17 2956
[12] Tao R, Li Y, Bai X 2012 IEEE Trans. Geosci. Remot. 50 3627
[13] Liu W, Guo L X, Wu Z S 2010 Chin. Phys. B 19 074102
[14] Tian W, Ren X C, Guo L X 2013 Chin. J. Comput. Phys. 30 134 (in Chinese) [田炜, 任新成, 郭立新 2013 计算物理 30 134]
[15] Zhang M, Zhao Y W, Zhao Y, Chen H 2013 IEEE Trans. Aero. Electr. Sys. 49 2046
[16] Chen H, Zhang M, Zhao Y W, Luo W 2010 IEEE Trans. Anten. Propag. 58 3751
[17] Iodice A, Natale A, Riccio D 2011 IEEE Trans. Geosci. Remot. 49 2534
[18] Martino G D, Riccio D, Zinno I 2012 IEEE Trans. Geosci. Remot. 50 630
[19] Clarizia M P, Bisceglie M D, Galdi C, Srokosz M 2012 IEEE Trans. Geosci. Remot. 50 960
[20] Franceschetti G, Guida R, Iodice A, Riccio D, Ruello G 2004 IEEE Trans. Geosci. Remot. 42 2385
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[1] Franceschetti G, Iodice A, Migliaccio M, Riccio D 1999 IEEE Trans. Anten. Propag. 47 1405
[2] Semchuk O Y, Grechko L G, Kunitskaya L Y, Gichan O I 2009 J. Appl. Spectro. 76 692
[3] Perna S, Iodice A 2011 IEEE Trans. Anten. Propag. 59 596
[4] IoIodice A, Natale A, Riccio D 2013 IEEE Trans. Anten. Propag. 61 2156
[5] Ruello G, Sanchez P B, Iodice A, Mallorqui J, Riccio D, Broquetas A, Franceschetti G 2010 IEEE Trans. Geosci. Remot. 48 1777
[6] Franceschetti G, Iodice A 1999 Radio Sci. 34 1043
[7] Franceschetti G, Iodice A, Riccio D, Ruello G 2005 IEEE Trans. Geosci. Remot. 43 1115
[8] Schelrath J H, denhofer P E 2005 Electro. Lett. 41
[9] Guo L X, Wang Y H, Wu Z S 2005 Acta Phys. Sin. 54 96 (in Chinese) [郭立新, 王运华, 吴振森 2005 物理学报 54 96]
[10] Ren X C, Guo L X 2009 Acta Phys. Sin. 58 1627 (in Chinese) [任新成, 郭立新 2009 物理学报 58 1627]
[11] Ren X C, Guo L X 2008 Chin. Phys. B 17 2956
[12] Tao R, Li Y, Bai X 2012 IEEE Trans. Geosci. Remot. 50 3627
[13] Liu W, Guo L X, Wu Z S 2010 Chin. Phys. B 19 074102
[14] Tian W, Ren X C, Guo L X 2013 Chin. J. Comput. Phys. 30 134 (in Chinese) [田炜, 任新成, 郭立新 2013 计算物理 30 134]
[15] Zhang M, Zhao Y W, Zhao Y, Chen H 2013 IEEE Trans. Aero. Electr. Sys. 49 2046
[16] Chen H, Zhang M, Zhao Y W, Luo W 2010 IEEE Trans. Anten. Propag. 58 3751
[17] Iodice A, Natale A, Riccio D 2011 IEEE Trans. Geosci. Remot. 49 2534
[18] Martino G D, Riccio D, Zinno I 2012 IEEE Trans. Geosci. Remot. 50 630
[19] Clarizia M P, Bisceglie M D, Galdi C, Srokosz M 2012 IEEE Trans. Geosci. Remot. 50 960
[20] Franceschetti G, Guida R, Iodice A, Riccio D, Ruello G 2004 IEEE Trans. Geosci. Remot. 42 2385
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