3-D Ultrasonic Localization of Transformer Patrol Robot Based on EMD and PHAT-β Algorithms

Abstract

This article is concerned with a hyperboloid 3-D localization method of the transformer patrol robot based on the empirical mode decomposition (EMD) of ultrasonic signals and phase transform-beta (PHAT- $\beta $ ) generalized cross correlation (GCC). A linear sensor array is first employed to receive ultrasonic signals emitted by robot. The received signals are decomposed into several intrinsic mode functions (IMFs) of different scales by EMD. According to the correlation degree between IMFs and the received signals, the IMFs with large correlation coefficients are subsequently selected to reconstruct the signals. Furthermore, the PHAT- $\beta $ GCC algorithm is used to estimate the time delay between the different sensors. Finally, multiple hyperboloids formed by sensors are intersected to accurately localize the robot. The simulation and experimental results demonstrate that the maximum relative errors in three typical positions are 5.6%, 4.8%, and 5.2%. The maximum localization error is less than 15 mm in a laboratory scale model with a size of length 800 mm, width 450 mm, and height 500 mm.