Broadband Sound Source Localization Via Non-Synchronous Measurements for Service Robots: A Tensor Completion Approach

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 with- out 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.