Broadband Sound Source Localisation via Non-Synchronous Measurements for Service Robots: A Tensor Completion Approach

Abstract

Constraint by the physical geometry, the lower and upper frequency bound and the scale of the scanning area of a microphone array are limited. Owing to its movable feature, for the service robots, achieving a wider working frequency range with a global view requires a virtually larger and denser array, which can be realised using non-synchronous measurements beamforming with a movable microphone array prototype. However, even when using the state-of-the-art method, it is challenging to localise multiple broadband sources, owing to the difficulty in selecting an appropriate operating frequency without any prior information about the target signal. Therefore, this letter proposes a tensor-completion-based non-synchronous measurements method for broadband multiple-sound-source localisation. The tensor data structure of the broadband signal is analysed, and an alternating direction method based on multiplier optimisation with a tensor multi-norm constraint is proposed. This algorithm can provide a sound map with a distinct global view of three different speech signal sources with high accuracy. Compared with the matrix-based optimisation method, the proposed method can significantly reduce the mean square error of the estimated source location.