Closed-form self-localization of asynchronous microphone arrays

Abstract

The utilization of distributed microphone arrays in many speech processing applications such as beamforming and speaker localization rely on the precise knowledge of microphone locations. Several selflocalization approaches have been presented in the literature but still a simple, accurate, and robust method for asynchronous devices is lacking. This work presents an analytical solution for estimating the positions and rotations of asynchronous loudspeaker equipped microphone arrays or devices. The method is based on emitting and receiving calibration signals from each device, and extracting the time of arrival (TOA) values. Utilizing the knowledge of array geometry in the TOA estimation is proposed to improve accuracy of translation. Results with measurements using four devices on a table surface demonstrates a mean translation error of 11 mm with standard deviation of 6 mm and mean z-axis rotation error of 0.11 (rad) with a standard deviation of 0.14 (rad) in contrast to computer vision annotations with 200 rotations and translation estimates.

Real-time sound source localisation for target tracking applications using an asynchronous microphone array

“…Most of them focus on computing the time delays between different microphone channels. Specific self-localisation methods for ad-hoc arrays of such devices have been proposed in [20] [21] [22] [23]. These methods can achieve high accuracy self-localisation geometry.…”

“…[20] and [23] provide closed-form estimators in contrast to iterative solutions. The method presented in [20] also considers acoustically determined orientation estimate of the device, which contains a microphone array. This method has been used in localisation of an asynchronous source in [24].…”

Simultaneous asynchronous microphone array calibration and sound source localisation

“…Most of these approaches can achieve high accuracy in microphone array selflocalisation. Both [6] and [9] provide closed-form estimators, in contrast to the standard iterative solution. The method presented in [6] also considers an acoustically determined, orientation estimate of a device that contains a microphone array.…”

“…Both [6] and [9] provide closed-form estimators, in contrast to the standard iterative solution. The method presented in [6] also considers an acoustically determined, orientation estimate of a device that contains a microphone array. This method has been used in localisation of an asynchronous source in [10].…”

“…Recent methods have started to relax these assumptions, for instance self-localisation approaches for ad-hoc arrays have been proposed in [6] [7] [8] [9]. Most of these approaches can achieve high accuracy in microphone array selflocalisation.…”