Geometry Calibration for Acoustic Transceiver Networks Based on Network Newton Distributed Optimization

Abstract

Geometry calibration for distributed acoustic sensor networks is becoming increasing popular in the signal processing community. In this paper, a distributed geometry calibration method based on network Newton distributed optimization is proposed for the acoustic transceiver networks where each node consists of a microphone array and a loudspeaker. After collecting the direction-of-arrival and time-difference-of-arrival measurements, a two-stage centralized cost function is formulated to estimate the geometrical configuration of networks, and the corresponding identifiability conditions are discussed. Next, to achieve the distributed calibration, a distributed cost function is established by splitting the centralized cost function into multiple local cost functions. Finally, the distributed geometry calibration is carried out by using network Newton distributed optimization. The proposed method can effectively estimate the geometry structure of acoustic transceiver networks in noisy and reverberant environments. Compared with the existing approaches, it implements the calibration process in a distributed manner, which requires only the local communication among nodes and does not need an external central processor. Experimental results show the validity of the proposed method.