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

Sensors

Carlos A. Luna¹  José A. Jiménez²  Daniel Pizarro²  Cristina Losada² 

[1] Electronics Department, High Polytechnic School, Alcalá University, Alcalá de Henares, Madrid, Spain;

关键词: principal component analysis (PCA);    generalized principal component analysis (GPCA);    reflector classification;    times-of-flight (TOFs);    ultrasonic sensors;   

DOI  :  10.3390/s100504825

来源: mdpi

【 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.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.