Title: Gas leakage acoustic source localisation with compressed sensing method in sensor networks

Authors: Yong Zhang; Tong Wang; Qi Chen; Yu Shi; Jinzhao Li; Liyi Zhang

Addresses: Information Engineering College, Tianjin University of Commerce, Tianjin 300134, China ' Information Engineering College, Tianjin University of Commerce, Tianjin 300134, China ' Information Engineering College, Tianjin University of Commerce, Tianjin 300134, China ' Information Engineering College, Tianjin University of Commerce, Tianjin 300134, China ' Information Engineering College, Tianjin University of Commerce, Tianjin 300134, China ' Information Engineering College, Tianjin University of Commerce, Tianjin 300134, China

Abstract: Aiming at solving the problem of the concentration signal hardly being compressive sensed directly in nonlinear gas diffusion environment, a compressed sensing direction of arrival (DOA) estimation method according to the acoustic characteristics of the gas leakage was proposed for source localisation. Firstly, the corresponding compressed sensing matrix and the DOA estimation model was established. Then, the sparse Bayesian recovery algorithm was designed for the DOA estimation of gas leakage acoustic source. Finally, the simulation results show that the proposed method could achieve an accurate DOA estimation of one or more gas leakage acoustic sources, and the sparse Bayesian recovery algorithm could effectively improve the estimation accuracy and robust performance with fewer amounts of samples compared to the orthogonal matching pursuit (OMP) algorithm.

Keywords: compressed sensing; DOA estimation; gas leakage acoustic source localisation.

DOI: 10.1504/IJSN.2020.111133

International Journal of Security and Networks, 2020 Vol.15 No.4, pp.206 - 213

Received: 27 Jan 2020
Accepted: 29 Jan 2020
Published online: 10 Nov 2020 *

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