Blind sampling rate offset estimation based on coherence drift in wireless acoustic sensor networks

Abstract

In this paper, a new approach for sampling rate offset (SRO) estimation between nodes of a wireless acoustic sensor network (WASN) is proposed using the phase drift of the coherence function between the signals. This method, referred to as least squares coherence drift (LCD) estimation, assumes that the SRO induces a linearly increasing phase-shift in the short-time Fourier transform (STFT) domain. This phase-shift, observed as a drift in the phase of the signal coherence, is applied in a least-squares estimation framework to estimate the SRO. Simulation results in different scenarios show that the LCD estimation approach can estimate the SRO with a mean absolute error of around 1%. We finally demonstrate that the use of the LCD estimation within a compensation approach eliminates the performance-loss due to SRO in a multichannel Wiener filter (MWF)-based speech enhancement task.