Abstract

In this paper, we introduce a novel acoustic source localization in a three-dimensional (3D) space, based on a direction estimation technique. Assuming an acoustic source at a distance from adjacent microphones, its waves spread in a planar form called a planar wavefront. In our system, the directions and steering angles between the acoustic source and the microphone array are estimated based on a planar wavefront model using a delay and sum beamforming (DSBF) system and an array of two-dimensional (2D) microelectromechanical system (MEMS) microphones. The proposed system is designed with parallel processing hardware for real-time performance and implemented using a cost-effective field programmable gate array (FPGA) and a micro control unit (MCU). As shown in the experimental results, the localization errors of the proposed system were less than 3 cm when an impulsive acoustic source was generated over 1 m away from the microphone array, which is comparable to a position-based system with reduced computational complexity. On the basis of the high accuracy and real-time performance of localizing an impulsive acoustic source, such as striking a ball, the proposed system can be applied to screen-based sports simulation.

Highlights

  • The screen-based simulation is becoming popular for various sports as it requires less play time and space in any weather condition [1,2]

  • The distance of 25 mm is close enough to assume that the sound wavefront is only 13 microelectromechanical system (MEMS) microphones

  • Only 13 MEMS microphones are required to estimate the direction-based beamforming algorithm in our microphone positioned in the center) are required to estimate the direction-based beamforming system, all of the 49 microphones are used to compare the accuracy of the location-based beamforming algorithm in our system, all of the 49 microphones are used to compare the accuracy of the locationtechnique used in [16]

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Summary

Introduction

The screen-based simulation is becoming popular for various sports as it requires less play time and space in any weather condition [1,2]. Most current commercial simulators are based on a computer vision technique using high-speed cameras [4,5] or a radar-based technique using the doppler effect [6]. These systems have a limited range to locate a ball position in three-dimensional (3D) space. Computer vision-based systems require a user to place a ball in the field of view of the cameras This restricts the ball placement to a small area on the ground and is not suitable for active sports such as soccer or baseball.

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