Gorman R P, Sawatari T
J Acoust Soc Am. 1985 Mar;77(3):1178-84. doi: 10.1121/1.392182.
The development of an accurate and efficient sonar-target classification system depends upon the identification of a set of signal features which may be used to discriminate important classes of signals. Feature selection can be facilitated through the identification of perceptual features used by human listeners in discriminating relevant sonar echoes. This study was conducted to establish a more reliable means of identifying perceptual features in terms of physical signal parameters as an initial step toward the development of an automatic sonar-target classification system. The results of an experiment involving eight subjects and six sonar echoes are presented. A model of the perceptual structure of these echoes was derived from subject similarity judgments using a multidimensional scaling (MDS) technique. It was found that three perceptual features accounted for the similarity judgments made by the human listeners. Echoes modified along candidate physical dimensions were employed to aid in the identification of perceptual dimensions in terms of physical signal parameters. The three perceptual features could be associated with signal parameters involving the amplitude envelope of the echoes.
准确高效的声纳目标分类系统的开发依赖于一组信号特征的识别，这些特征可用于区分重要的信号类别。通过识别人类听众在区分相关声纳回波时使用的感知特征，可以促进特征选择。本研究旨在建立一种更可靠的方法，根据物理信号参数识别感知特征，作为开发自动声纳目标分类系统的第一步。本文呈现了一项涉及八名受试者和六种声纳回波的实验结果。使用多维标度（MDS）技术从受试者的相似性判断中得出了这些回波的感知结构模型。结果发现，三种感知特征可以解释人类听众做出的相似性判断。沿着候选物理维度修改后的回波被用来帮助根据物理信号参数识别感知维度。这三种感知特征可能与涉及回波幅度包络的信号参数相关。
