Sound Source Localization in Wide-Range Outdoor Environment Using Distributed Sensor Network

• Published in: IEEE sensors journal Vol. 20; no. 4; pp. 2234 - 2246
• Main Authors: Faraji, Mohammad Mahdi, Shouraki, Saeed Bagheri, Iranmehr, Ensieh, Linares-Barranco, Bernabe
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.02.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Array signal processing; Audio signals; Beamforming; beamforming method; Calibration; data fusion; Delays; distributed sensor network; Distributed sensor systems; fuzzy logic; Global Positioning System; Localization; Microphone arrays; Modules; Nodes; Performance evaluation; Sensor arrays; Sensors; Sound source localization; Sound sources; Sound waves; Trajectory analysis
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2019.2950447

Sound source localization has always been one of the most challenging subjects in different fields of engineering, one of the most important of which being tracking of flying objects. This article focuses on sound source localization using fuzzy fusion and a beamforming method. It proposes a new fuzzy-based algorithm for localizing a sound source using distributed sensor nodes. Eight low-cost sensor nodes have been constructed in this study each of which consists of a microphone array to capture sound waves. Each node is able to record audio signals synchronously on an SD card to evaluate different algorithms offline. However, the sensor nodes are designed to be able to estimate the location of the sound source in real-time. In the proposed algorithm, every node estimates the direction of the sound source. Moreover, a calibration algorithm is used for extracting the orientation of sensor nodes to calibrate the estimated directions. The calibrated directions are fuzzified and then used for localizing the sound source by fuzzy fusion. An experiment was designed based on localizing a flying quadcopter as a moving sound source to evaluate the performance of the proposed algorithm. The flying trajectory was then estimated and compared with the target trajectory extracted from the GPS module mounted on the quadcopter. Comparing the estimated sound source with the target location, a mean distance error of <inline-formula> <tex-math notation="LaTeX">{6.03}{m} </tex-math></inline-formula> was achieved in a wide-range outdoor environment with the size of <inline-formula> <tex-math notation="LaTeX">{240}\times {160}\times {80} \,\,{m}^{{3}} </tex-math></inline-formula>. The achieved mean distance error is reasonable regarding the mean precision of the GPS module. The practical results illustrate the effectiveness of the proposed approach in localizing a sound source in a wide-range outdoor environment.