共查询到16条相似文献,搜索用时 53 毫秒
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首先描述了Del Grosso算法和C.C.Leroy算法计算海洋声速及其特点(貌似不通);然后利用美国国家海洋数据中心发布的WOA09数据,分别采用Del Grosso算法和C.C.Leroy算法计算西太平洋海域某点的海洋声速剖面,结果表明两种算法具有相同的个位数字精度。与Del Grosso算法相比,C.C.Leroy算法效率更高,不需要深度与压强的转换。 相似文献
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海洋中的声速剖面是影响水声设备效能的重要环境因素之一,声速剖面的自动分类和区划对海洋环境的应用意义重大.依据浅海30分方区按月统计声速剖面,通过归一化处理和Akima差值采样,建立了各方区按月归化后声速剖面的分层梯度样本集,并应用多种系统聚类算法分别对分层梯度样本集进行分析;计算各种算法在不同聚类数水平下聚类结果的总的类内离差和,依据总的类内离差和变化曲线拐点对应的聚类数目,结合分类结果确定浅海声速剖面最优聚类数目.对大量历史统计声速剖面数据的分析结果表明,该方法得到的聚类结果与人工经验分类结果吻合较好. 相似文献
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以海区30'网格方区多年月平均统计的声速剖面作为原始数据集,提取声速剖面的表层、主跃层和深海等温层分层结构特征,把我国近海及其邻近海域预分为Ⅰ,Ⅱ和Ⅲ类区。对Ⅱ,Ⅲ类区声速剖面,应用有序样本聚类算法分别进行表层分离。根据各类区的表层声速剖面数据,通过归一化处理和Akima差值采样得到梯度剖面,建立起按月归一化后的声速剖面分层梯度样本集,并应用系统聚类法和SOFM神经网络方法分别进行聚类分析,再根据分类结果并结合各类型海区的声学特点,得到各类型海区声速剖面的典型类型。通过对大量历史数据的分析结果表明,该方法为自动分类海洋声速剖面提供了一条有效路径,弥补了长期以来海洋声速剖面主要依靠人工分类的不足。 相似文献
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AbstractIn long baseline (LBL) positioning system, errors due to uncertain sound speed are the major facts to its positioning accuracy. In this study, the problem is solved by setting acoustic signal travels between the target and different hydrophones with different sound speed and using particle swarm optimization algorithm to solve the multi-parameter optimization problem to obtain the sound speeds. Presented simulation results show that the proposed algorithm can effectively improve the positioning accuracy of the LBL system compared to existing algorithms and its computational efficiency is high enough. 相似文献
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A new method of positioning underwater static objects is presented based on Global Positioning System (GPS) acoustics. It adopts a model in which the ranging errors follow a quadratic relation with the travel time of acoustic signals. A least squares technique is used to estimate the effective sound speed. The precise location of an object can then be made. The simulation shows that the method is capable of determining the three-dimensional position with an accuracy of 5 cm in a water depth of 500 m. The operating time is respectively 5–10 minutes in 50–100 m depth and 20–30 minutes in 500 m depth. 相似文献