Acoustic benchmark validation of GRASP ASW search plans

K.P. Hemsteter, D. DelBalzo
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引用次数: 8

Abstract

A genetic algorithm is used in non-homogeneous and anisotropic environments to nearly optimize sonar search tracks. The optimization metric is maximum cumulative detection probability for a specified sonar (passive or active) against a target with specified characteristics (acoustic and tactical) during a fixed time period. This application for search planning is named GRASP, for Genetic Range-dependent Algorithm for Search Planning. A validation of GRASP solutions in various ocean environments is shown under benchmark conditions, i.e., fairly simple synthetic environments and a simple target distribution. Directional, range-dependent sonar performance (signal excess) is estimated from parabolic equation calculations of transmission loss. The search tracks produced by the genetic algorithm are generally intuitive; they usually remain in high detection areas. When track solutions are counter-intuitive, we explain unexpected behavior (e.g., zigzag turns, tracks offset from symmetric features, and occasional departures from high detection areas) in terms of details in the acoustic field.
GRASP ASW搜索方案的声学基准验证
在非均匀和各向异性环境下,采用遗传算法对声纳搜索轨迹进行近似优化。优化度量是在固定时间段内,指定声纳(被动或主动)对具有指定特征(声学和战术)的目标的最大累积探测概率。这个搜索规划的应用程序被命名为GRASP,即搜索规划的遗传范围依赖算法。在基准条件下,即相当简单的合成环境和简单的目标分布,展示了各种海洋环境中GRASP解决方案的验证。方向,距离相关的声纳性能(信号过剩)是由传输损耗的抛物线方程计算估计的。遗传算法产生的搜索轨迹一般是直观的;它们通常停留在高检出率地区。当轨道解决方案是反直觉的,我们解释了意想不到的行为(例如,之字形转弯,轨道偏离对称特征,偶尔偏离高检测区域)在声场的细节方面。
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