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首页> 外文期刊>The Journal of the Acoustical Society of America >Parameter estimation using multifrequency range-dependent acoustic data in shallow water
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Parameter estimation using multifrequency range-dependent acoustic data in shallow water

机译:利用多频范围内的浅水声数据进行参数估计

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摘要

The estimation of all forward model parameters—geometric, geoacoustic, and ocean sound speed—by the inversion of acoustic field observations is considered. The data was taken at a mildly range-dependent shallow water site in the Mediterranean Sea. The inversion is based on data from a vertical array and carried out using information at multiple frequencies. Global optimization using a directed Monte Carlo search based on genetic algorithms and the Bartlett objective function is used. All geometric parameters are well determined, a range-dependent geoacoustic model is determined, and the ocean sound speed is estimated. Comparisons of the observed pressure field as a function of depth and the predicted field show good agreement. The use of observations at multiple frequencies provides considerable stability for the estimated parameters. Optimization of only geometric and geoacoustic parameters in a range-independent environment is found to be satisfactory at the lower frequencies (165–175 Hz), but for the higher frequencies (325–335 Hz) optimization of additional parameters by inclusion of either a range-dependent forward model or the ocean-sound-speed profile seems essential for successful inversion.
机译:考虑通过反演声场观测来估计所有正向模型参数(几何,地球声学和海洋声速)。数据是在地中海的一个温和范围相关的浅水站点获得的。反转基于来自垂直阵列的数据,并使用多个频率的信息进行。使用基于遗传算法和Bartlett目标函数的定向蒙特卡洛搜索进行全局优化。确定所有几何参数,确定与范围相关的地声模型,并估算海洋声速。观察到的作为深度函数的压力场与预测场的比较显示出很好的一致性。在多个频率上使用观测值可为估计的参数提供相当大的稳定性。在较低的频率(165–175 Hz)下,仅在与范围无关的环境中仅几何和地声参数的优化被认为是令人满意的,但是对于较高的频率(325–335 Hz),通过包括任一范围的优化其他参数依赖的前向模型或海声速度剖面对于成功反演似乎至关重要。

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