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Sparse-increment iteration-based sound velocity profile estimation with multi-beam bathymetry systems

机译:基于多波束测深系统的基于稀疏增量迭代的声速剖面估计

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This paper presents a method to estimate the sound velocity profile (SVP) of the water column along with the bathymetry using overlapping swaths obtained from a multi-beam system. The method exploits the terrain deviations in the overlapped regions of different survey tracks. Such deviation is closely related to the SVP errors, and hence by minimizing the deviations, the SVP can be updated from the prior value. Furthermore, a sparse-increment iteration-based method is developed to solve the estimation problem, which is quite efficient in computation. Both simulated and experimental data processing results demonstrate that the proposed method can yield an SVP estimate converging to the true SVP value after a limited number of iterations while generating more precise depth measurements.
机译:本文提出了一种方法,该方法使用从多波束系统获得的重叠条带来估算水柱的声速剖面(SVP)以及测深法。该方法利用了不同测量轨迹的重叠区域中的地形偏差。这种偏差与SVP误差密切相关,因此,通过最小化偏差,可以从先前值更新SVP。此外,开发了一种基于稀疏增量迭代的方法来解决估计问题,该方法在计算中非常有效。仿真和实验数据处理结果均表明,所提出的方法可以在有限次数的迭代之后产生收敛到真实SVP值的SVP估计,同时生成更精确的深度测量值。

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