Low-frequency sound source localization in enclosed space based on time reversal method

Abstract

This study investigates sound source localization (SSL) in enclosed space at low frequencies. Reverberation and noise are important factors that affect localization result. Time reversal technology has the characteristics of compensating the multipath effect and adaptive focus, therefore, it can realize (SSL) in enclosed space. In order to improve the spatial resolution of localization, the recovery of the second transmitting signal received after time reversal is completed by the compressive sensing algorithm. We propose time reversal sparse Bayesian learning (TR-SBL) method to solve the problem of SSL. Firstly, time reversal focusing model of sound source propagation in the enclosed space is established. Then compressive sensing algorithm is performed on the second received signal, a sparse Bayesian framework is used to solve the localization problem. The time reversal method can overcome the reverberation interference in the enclosed space, and the compressive sensing algorithm can improve the spatial resolution. A series of simulations, which can be compared with the time reversal method and L1 norm method, are carried out to verify the localization performance of the proposed method, including simulations of sound sources with different frequencies, signal-to-noise ratios (SNRs), absorption coefficients, and positions. The algorithm is also evaluated in a reverberation chamber using sound sources with different frequencies. The numerical simulations and experimental results show that the proposed method achieves good localization performance in a low-SNR and reverberation environment, the spatial resolution is up to 0.1 m for a sound source with a frequency of 125 Hz.