星载合成孔径雷达对海内波检测与参数估计

发布时间：2018-10-30 17:22

【摘要】：合成孔径雷达(Synthetic Aperture Radar,SAR)具有全天时、全天候、观测范围广的特点,在遥感领域具有越来越广泛的应用。内波(Internal Waves,IW)是指在流体内部发生的一种波动形式,而海洋内波就是一种典型的内波形式。由于海洋内波具有较大的幅度,传递巨大的能量,在海洋开发、船只航线规划乃至国防军事领域都具有重要的研究意义。并且,随着分辨率的不断提高,SAR对海面的观察能力逐渐提升,包含的信息也更加的丰富。由于电磁波无法深入到海洋中直接对海洋内波进行观测,所以仅能通过海洋表面的变化,推导海洋海洋内波的相关参数。但是,由于从海洋内波到海洋表面,再到接收机的过程会引入较多的干扰因素,使得在运算量和估计的准确性上都存在较大的可改进性。基于上面的原因,本课题在分析内波的形成机理、SAR对海洋表面的成像模型基础上,着眼于利用SAR数据,探究在SAR参数对内波图像的影响、利用图像处理的方法在SAR图像中进行在图像内定位内波的位置、使用期望最大化算法对统计直方图进行模型拟合以及在SAR图像中进行内波参数提取的方法。本文的主要研究内容如下:论文首先建立海洋内波产生的模型,并推导其所满足的动力学方程,求取满足方程的稳态解。对海洋表面在SAR观测情况下的三种不同成像模型进行了介绍;同时,针对接收幅度过小的情况,引入调制深度的概念,利用仿真工具和特定的内波模型以及成像模型,通过针对沿内波传播方向上极值点随着参数变化的趋势,分析参数对成像效果带来的影响,寻找最佳的雷达观测参数组合。其次,利用简单图像处理的方法对SAR图像进行预处理,分离出海洋区域;利用基于马尔科夫随机场的分割方法对含有内波条纹的图像进行纹理增强,并借助基于Radon变换的纹理检测方法,从大场景的SAR图像中,快速定位内波在图像中的位置;针对SAR图像分辨率提升带来统计直方图出现多模态、拖尾严重的现象,结合之前学者提出的广义混合模型,利用期望最大化的方法进行分布模型的参数估计,为SAR图像的分类、降噪和目标检测提供辅助作用;从估计结果与实际结果的均方差衡量估计的结果,通过迭代次数衡量方法的计算量。最后,利用已知的先验模型和获得的图像剖面数据,采用曲线拟合的方式,对模型中的参数进行确定;同时针对内波图像剖面的非线性特点,利用基于经验模态分解的方法,分解得到内波分量,并利用该分量对内波参数进行估计;根据干涉的概念以及地面运动速度和干涉相位的关系,利用干涉相位提取海洋表面的速度信息;提出基于仿真迭代的参数估计方法,对内波的参数进行迭代估计。
[Abstract]:Synthetic Aperture Radar (Synthetic Aperture Radar,SAR) has been widely used in the field of remote sensing because of its wide range of observation and all-weather. Internal wave (Internal Waves,IW) is a form of internal wave occurring in fluid, and ocean wave is a typical form of internal wave. Because of the large amplitude of ocean internal wave and the transmission of huge energy, it is of great significance in the field of ocean exploitation, ship route planning and even national defense and military affairs. Moreover, with the improvement of resolution, the ability of SAR to observe sea surface is improved gradually, and the information is more abundant. Because the electromagnetic wave can not penetrate into the ocean directly to observe the ocean internal wave, it can only deduce the relevant parameters of the ocean internal wave by the variation of the ocean surface. However, the process from the ocean internal wave to the ocean surface, and then to the receiver, will introduce more interference factors, which makes it possible to improve the computational complexity and the accuracy of the estimation. Based on the above reasons, based on the analysis of the formation mechanism of internal waves and the imaging model of SAR on the ocean surface, we focus on the use of SAR data to explore the influence of SAR parameters on the internal wave images. The method of image processing is used to locate the position of the internal wave in the SAR image, the model fitting of the statistical histogram and the extraction of the internal wave parameters in the SAR image are carried out by using the expectation maximization algorithm. The main contents of this paper are as follows: firstly, the model of ocean internal wave generation is established, and the satisfied dynamic equation is derived, and the steady-state solution of the satisfied equation is obtained. Three different imaging models of ocean surface under SAR observation are introduced. At the same time, the concept of modulation depth is introduced in the case of too small receiving amplitude. By using the simulation tool, the specific internal wave model and the imaging model, the trend of the extreme point changing with the parameters along the direction of the internal wave propagation is analyzed. The effect of the parameters on the imaging effect is analyzed and the best combination of radar observation parameters is found. Secondly, the SAR image is preprocessed by the simple image processing method, and the ocean area is separated. The segmentation method based on Markov random field is used to enhance the texture of the image with internal wave fringes. With the help of texture detection method based on Radon transform, the position of internal wave in large scene SAR image is quickly located. Aiming at the phenomenon of multi-modal and serious trailing in the statistical histogram caused by the resolution enhancement of SAR image, combined with the generalized mixed model proposed by the previous scholars, the parameter estimation of the distribution model is carried out by using the method of expectation maximization, which is the classification of the SAR image. Noise reduction and target detection provide auxiliary effect; The estimated results are measured from the RMS of the estimated results and the actual results, and the computational complexity of the method is measured by the number of iterations. Finally, using the known prior model and the obtained image profile data, the parameters in the model are determined by the way of curve fitting. At the same time, according to the nonlinear characteristics of the internal wave image profile, the internal wave component is obtained by using the empirical mode decomposition method, and the internal wave parameters are estimated by this component. According to the concept of interference and the relationship between the velocity of ground motion and the phase of interference, the velocity information of ocean surface is extracted by using the phase of interference, and a parameter estimation method based on simulation iteration is proposed to estimate the parameters of internal wave iteratively.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN958

【参考文献】