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A Novel Vessel Velocity Estimation Method Using Dual-Platform TerraSAR-X and TanDEM-X Full Polarimetric SAR Data in Pursuit Monostatic Mode

机译:追踪单静态模式下使用双平台TerraSAR-X和TanDEM-X全极化SAR数据的新型船速估算方法

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In this paper, we demonstrate that the spaceborne dual-platform TerraSAR-X (TSX) and TanDEM-X (TDX) pursuit monostatic mode full polarimetric (full-pol) synthetic aperture radar (SAR) data with a time lag can be used to monitor maritime traffic. For single polarization (single-pol) SAR data, the performance of vessel velocity estimation is mainly determined by 2-D cross correlation of SAR intensity data. As the sea clutter is changing dynamically during the TSX/TDX data acquisition, the correlation between two dual-platform images decreases significantly. We may get unstable or incorrect estimations of vessel velocity, especially under a higher wind condition. For solving this problem, we propose an object-oriented polarimetric likelihood ratio test (PolLRT) method based on the complex Wishart distribution. The proposed method makes PolLRT statistics of the detected target pixels for eliminating the effect of varied sea clutter. Two pairs of full-pol SAR data sets covering the Strait of Gibraltar acquired by dual-platform TSX/TDX in pursuit monostatic mode with a time lag of approximately 10 s are selected for the experiments. The experimental results demonstrate that the proposed PolLRT method has a better performance than that of the classical normalized cross correlation (NCC) method with VV polarization SAR data and the mutual information (MI) method with full-pol SAR data. Specifically, under the lower wind condition, the correct estimation rate of the NCC, the MI, and the proposed PolLRT methods are 85.7%, 57.1%, and 100%, respectively; under the relatively higher wind condition, the correct estimation rate of the above three methods are 48.8%, 23.2%, and 90.1%, respectively.
机译:在本文中,我们证明了具有时滞的星载双平台TerraSAR-X(TSX)和TanDEM-X(TDX)追求单静态模式全极化(full-pol)合成孔径雷达(SAR)数据可用于监控海上交通。对于单极化(single-pol)SAR数据,船速估计的性能主要取决于SAR强度数据的二维互相关。由于海浪杂波在TSX / TDX数据采集过程中动态变化,因此两个双平台图像之间的相关性显着降低。我们可能会获得不稳定或不正确的船速估计值,尤其是在较高风况下。为了解决这个问题,我们提出了一种基于复杂Wishart分布的面向对象的极化似然比检验(PolLRT)方法。所提出的方法对检测到的目标像素进行PolLRT统计,以消除海杂波变化的影响。实验选择了两对全双极化SAR数据集,这些数据集是通过双平台TSX / TDX在追求单静态模式下以约10 s的时滞获取的,涵盖了直布罗陀海峡。实验结果表明,与采用VV极化SAR数据的经典归一化互相关(NCC)方法和采用全极化SAR数据的互信息(MI)方法相比,所提出的PolLRT方法具有更好的性能。具体而言,在低风条件下,NCC,MI和建议的PolLRT方法的正确估计率分别为85.7%,57.1%和100%。在相对较高的风况下,以上三种方法的正确估计率分别为48.8%,23.2%和90.1%。

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