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Acoustic species identification of schooling fish

机译：养殖鱼类的声种鉴定

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The development of methods for the acoustic identification of fish is a long-term objective aimed at reducing uncertainty in acoustic-survey estimates. The relative frequency response r(f) measured simultaneously at several frequencies is one of the main acoustic features that characterize the targets, but the relationship between nearest neighbours, school morphology, and environmental and geographical data are also important characteristics in this context. The number of acoustic categories that can be separated with a high spatial resolution is limited by the stochastic nature of the measurements. Because the acoustic categorization of larger ensembles is more reliable than for single targets, spatial smoothing of the backscattering within the school boundaries before that process allows the separation of more categories than is possible with the raw, highly resolved data. Using the mean r(f) of an entire school gives even more reliable categorization, but determining whether or not the school is monospecific sets a new challenge. This problem is evaluated here. The methods are tested and verified. Identification of acoustic categories with similar acoustic properties is done for schooling fish, although the results have limited spatial resolution. The reliability of the categorization is further improved when knowledge of school morphology and geographical distribution of the species are taken into account.
机译：鱼类声学识别方法的发展是一个长期目标，旨在减少声学调查估计中的不确定性。在几个频率上同时测量的相对频率响应r（f）是表征目标的主要声学特征之一，但是在这种情况下，最近邻居，学校形态以及环境和地理数据之间的关系也是重要的特征。可以以高空间分辨率分离的声学类别的数量受到测量结果的随机性的限制。因为较大的乐团的声音分类比单个目标的声音分类更可靠，所以在此过程之前，在学校范围内进行反向散射的空间平滑允许分离比原始的高度解析的数据更多的类别。使用整个学校的均值r（f）可以提供更可靠的分类，但是确定学校是否为单一学校将带来新的挑战。在这里评估此问题。该方法已经过测试和验证。尽管放养的空间分辨率有限，但仍对鱼类进行了声学特性相似的声学类别识别。当考虑到学校形态和物种地理分布的知识时，分类的可靠性将进一步提高。

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