SAR图像反演浅海地形的一种改进方法

传统的SAR图像浅海地形反演方法仅采用迭代模型求解水深,收敛速度较慢。采用基于AH模型获得初步的浅海水深,然后带入迭代模型进行优化的方法,加快了反演收敛速度。基于该改进方法,利用1景ERS-2和1景ENVISAT数据,对某海域的水深进行了反演。与实测水深相比,此方法获得的水深的平均相对误差分别为8.9%和10.8%,同时有效的减少了迭代次数。另外研究发现,采用地形的绝对变化误差作为SAR浅海地形反演精度的指标不够合理。因此采用去除反映地形整体走势的基准面后的相对地形变化误差作为浅海地形反演精度的一个指标。

Improved retrieval method for shallow sea topography using SAR image

Traditional synthetic aperture radar （SAR） underwater topography detection is developed by optimizing the depth with iteration model only,and the algorithm＇s convergence speed is too slow. AH model is used to get the first guess shallow water depth as an improvement,and then the depth is optimized with iteration model, thus accelerates the iteration. Based on this algorithm,water depth is retrieved with 1 set of ERS-2 and 1 set of ENVISAT SA~ image. The relative mean errors between the retrieved depths and measured ones are 8. 9~ and 10. 8~ respectively, and the iteration times reduced. It is indicated that the absolute error between the retrieved depth and measured depth is not a good standard to evaluate the accuracy of water depth retrieved from the SAR image. Thus the relative change of the topography is taken as a standard of the retrieval accuracy hy taking off the base topography depth.