Average acoustic beamforming in car cabins: An automatic system for acoustic mapping over 3D surfaces

This paper describes a microphone array-based measurement systems for mapping noise sources in car cabins. The system exploits the average beamforming concept, a measuring/processing method that makes it possible to significantly reduce ghost sources caused by the presence of reflective surfaces and to improve the source localization task in closed environments. The average beamforming procedure consists in sampling a stationary acoustic field moving a microphone array of known geometry in different locations, so to perform a statistical processing out of the beamforming results obtained from each measurement position. Since the calculation is based on the relative distance between each microphone and the calculation grid, the identification of the array position inside the measurement environment is of primary importance. In an interior noise source localization application, which is quite typical of the automotive sector, this translates in the necessity of an accurate knowledge of both the microphone array locations and the cabin internal geometry, since the calculation grid is typically made to coincide with the cabin internal surfaces. The solution proposed in this paper involves a coordinate measurement system, based on the Microsoft Kinect (first release 2010) device, to measure both microphone array positions and cabin surface in the same reference frame. A calibration procedure was specifically performed on the Kinect system in order to transform this compact and cheap device in a coordinate measuring system. The performance of the whole strategy are discussed on the basis of tests performed in a real car environment in which a speaker was exploited as target source. Results provided demonstrate the effectiveness of the proposed method.