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GPCA vs. PCA in Recognition and 3-D Localization of Ultrasound Reflectors

机译:GPCA与PCA在超声反射器的识别和3-D定位中的比较

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摘要

In this paper, a new method of classification and localization of reflectors, using the time-of-flight (TOF) data obtained from ultrasonic transducers, is presented. The method of classification and localization is based on Generalized Principal Component Analysis (GPCA) applied to the TOF values obtained from a sensor that contains four ultrasound emitters and 16 receivers. Since PCA works with vectorized representations of TOF, it does not take into account the spatial locality of receivers. The GPCA works with two-dimensional representations of TOF, taking into account information on the spatial position of the receivers. This report includes a detailed description of the method of classification and localization and the results of achieved tests with three types of reflectors in 3-D environments: planes, edges, and corners. The results in terms of processing time, classification and localization were very satisfactory for the reflectors located in the range of 50–350 cm.
机译:在本文中,提出了一种使用从超声换能器获得的飞行时间(TOF)数据对反射器进行分类和定位的新方法。分类和定位的方法基于应用于从包含四个超声发射器和16个接收器的传感器获得的TOF值的广义主成分分析(GPCA)。由于PCA使用TOF的矢量化表示,因此未考虑接收器的空间位置。考虑到有关接收器空间位置的信息,GPCA使用TOF的二维表示。该报告详细描述了分类和定位方法以及在3-D环境中使用三种类型的反射器进行测试的结果:平面,边缘和角。对于位于50-350 cm范围内的反射镜,在处理时间,分类和定位方面的结果非常令人满意。

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