Asynchronous Microphone Array Calibration using Hybrid TDOA Information
<|reference_start|>Asynchronous Microphone Array Calibration using Hybrid TDOA Information: Asynchronous microphone array calibration is a prerequisite for many audition robot applications. A popular solution to the above calibration problem is the batch form of Simultaneous Localisation and Mapping (SLAM), using the time difference of arrival measurements between two microphones (TDOA-M), and the robot (which serves as a moving sound source during calibration) odometry information. In this paper, we introduce a new form of measurement for microphone array calibration, i.e. the time difference of arrival between adjacent sound events (TDOA-S) with respect to the microphone channels. We propose to use TDOA-S and TDOA-M, called hybrid TDOA, together with odometry measurements for bath SLAM-based calibration of asynchronous microphone arrays. Extensive simulation and real-world experiments show that our method is more independent of microphone number, less sensitive to initial values (when using off-the-shelf algorithms such as Gauss-Newton iterations), and has better calibration accuracy and robustness under various TDOA noises. Simulation results also demonstrate that our method has a lower Cram\'er-Rao lower bound (CRLB) for microphone parameters. To benefit the community, we open-source our code and data at https://github.com/AISLAB-sustech/Hybrid-TDOA-Calib.<|reference_end|>
@article{zhang2024asynchronous,
    title={Asynchronous Microphone Array Calibration using Hybrid TDOA Information},
    author={Chengjie Zhang, Jiang Wang, and He Kong},
    journal={arXiv preprint arXiv:2403.05791},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.05791},
    primaryClass={eess.AS cs.SD}
}