A Double-cross-correlation Processor for Blind Sampling Rate Offset Estimation in Acoustic Sensor Networks
Aleksej Chinaev, Philipp Thüne, Gerald Enzner
Abstract
Signal synchronization in wireless acoustic sensor networks requires an accurate estimation of the sampling rate offset (SRO) inevitably present in signals acquired by sensors of ad-hoc networks. Although some sophisticated methods for blind SRO estimation have been recently proposed in this very young field of research, there is still a need for the development of new ideas and concepts especially regarding robust approaches with low computational complexity. We therefore propose a novel time-domain method based on the calculation of a double-cross-correlation function in this contribution. Experimental evaluation of the introduced approach in a challenging acoustic environment and comparison with a state-of-the-art frequency-domain method confirms the high accuracy and low computational load of the proposed technique.
BibTeX
@inproceedings{icassp2019_adoublecrosscorr,
title = {A Double-cross-correlation Processor for Blind Sampling Rate Offset Estimation in Acoustic Sensor Networks},
author = {Aleksej Chinaev and Philipp Thüne and Gerald Enzner},
booktitle = {ICASSP 2019},
year = {2019}
}