一种多波束测深声线跟踪自适应分层方法

为解决声线跟踪精度与计算量之间的矛盾,在常梯度分层声线跟踪法的基础上,提出了一种适用于多波束测深的声线跟踪自适应分层方法,即利用Douglas-Peucker算法对原始声速剖面数据进行筛选分层。给出了不同阈值的分层结果,并对等间隔分层与自适应分层的声线跟踪结果进行了比较。实验结果表明,自适应分层法能够顾及到声速结构变化规律,有效提取声速变化节点,克服了人工选点的不足;在相同计算量情况下,自适应分层法声线跟踪精度要优于传统的等间隔分层法。本方法能够有效解决声线跟踪精度与计算量之间的矛盾,具有良好的工程应用价值。

A Self-adapting Division Method for Ray-tracing of Multibeam Echosounding

In order to solve the conflict between the ray-tracing precision and the amount of computation,a self-adapting division method for ray-tracing of multibeam survey is presented.With the Douglas-Peucker algorithm,the original sound speed profile data is selected and divided,the division results with different threshold are given,and the ray-tracing results with equal interval division and self-adapting division are compared.The experiments show that the self-adapting division method can consider the change laws of sound structure,extract the sound speed changing node effectively and overcome the deficiency of artificial selection.In the case of same amount of computation,the ray-tracing accuracy of the self-adapting division method is better than the traditional equal interval division method.The method with a good engineering application value can effectively solve the conflict between the ray-tracing precision and the amount of computation.