Sound Localization Based on Acoustic Source Using Multiple Microphone Array in an Indoor Environment

Abstract

Sound signals have been widely applied in various fields. One of the popular applications is sound localization, where the location and direction of a sound source are determined by analyzing the sound signal. In this study, two microphone linear arrays were used to locate the sound source in an indoor environment. The TDOA is also designed to deal with the problem of delay in the reception of sound signals from two microphone arrays by using the generalized cross-correlation algorithm to calculate the TDOA. The proposed microphone array system with the algorithm can successfully estimate the sound source’s location. The test was performed in a standardized chamber. This experiment used two microphone arrays, each with two microphones. The experimental results prove that the proposed method can detect the sound source and obtain good performance with a position error of about 2.0~2.3 cm and angle error of about 0.74 degrees. Therefore, the experimental results demonstrate the feasibility of the system.

Recent Advancements in Indoor Positioning and Localization

“…Sensor Approach [1] Positioning Acoustic Time difference of arrival [2] Channel modeling Visible light Bimodal Gaussian distribution in line of sight and non-line of sight [3] Energy optimization -Macro model for energy optimization [4] Positioning Wireless Improved K nearest neighbor [5] Positioning Smartphone sensors Analytical review…”

“…The study in [1] utilizes sound signals for indoor localization, which is one of the most widely experimented with and deployed positioning and localization technologies. Based on the direction of the sound and the traveling time of the sound, it can provide highly accurate positioning.…”

Acoustic source localization through the data fusion with multi-distributed microphone arrays

“…Therefore, the multi-microphone arrays' structure has emerged for completing more complex sound localization tasks (such as sniper localization system, rescue robots in earthquake stricken areas, multi robot cooperation system, etc.) [23][24] . However, it increases the complexity of the design and deployment, the amount of data acquisition and calculation.…”

Sound Source Localization Based on Multi-Channel Cross-Correlation Weighted Beamforming

“…The time delay estimation method achieves the source location based on the arrival time difference [ 10 ]. In [ 11 ], sound source localization in an indoor environment is completed by using two dual-element arrays to estimate time delay. However, the time delay estimation method is susceptible to noise.…”