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

DOI码：10.1109/TGRS.2019.2904465

发表刊物：IEEE Transactions on Geoscience and Remote Sensing

关键字：Polarimetric likelihood ratio test (PolLRT), polarimetric synthetic aperture radar (SAR), vessel detection

摘要：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.

合写作者：Li Xiaofeng, Zhu Jianjun, Li Zhiwei

论文类型：期刊论文

通讯作者：Shen Peng

学科门类：工学

文献类型：J

卷号：57

期号：8

页面范围：6130-6144

是否译文：否

发表时间：2019-04-11

收录刊物：SCI